Anthropic’s latest AI model, Claude Fable 5, represents a significant step forward in autonomous reasoning, coding, and research capabilities. Unlike earlier generations of AI assistants, Fable 5 can handle complex, multi-step tasks with greater independence, helping businesses accelerate development, research, and operational workflows.

Coding

One of Fable 5’s best features is its ability to code to a more advanced level than other agentic AI agents that have come before it. Tasks that had previously taken software engineers days or even months can be done in a matter of hours, such as coding websites and developing web apps.

It can also work autonomously for longer periods of time than other AI models without the need for human input or prompts due to its advanced capabilities. Anthropic used a case study to test Fable 5’s software engineering capabilities before releasing it to the public, and here’s what they found.

“During early testing, Stripe reported that Fable 5 compressed months of engineering into days. In a 50-million-line Ruby codebase, the model performed a codebase-wide migration in a day that would otherwise have taken a whole team over two months by hand.”

This is invaluable for marketing businesses who would have to spend months of time and manpower towards development costs. It can also help digital marketers and web developers with other coding tasks in the industry such as:

• Assist in building websites
• Prototyping web apps
• Building landing pages from a brief
• Creating custom SEO tools and dashboards
• Integrating CRMs with marketing platforms

Research

The autonomous nature of Fable 5 means it is also capable of performing advanced research tasks and can even be used to help train users in complex tasks and new skills, including web development and SEO. It’s not only limited to training, though; it can also aid in complex digital marketing research tasks. Some SEO tasks Fable can help with include:

• Competitor analysis
• Content gap analysis
• Audience research
• Market trend identification
• Industry report summarisation
• Technical SEO audits

How does this affect Digital Marketers?

The ability to edit and build digital websites and web apps at scale allows marketers to be able to develop much more efficiently, while Fable’s enhanced research capabilities now make marketing tasks such as keyword research, SEO and data analysis so much less complex and streamlined if used in the right way.

For most of the past two decades, SEO success had a relatively simple definition: rank higher, get more traffic. Position one was the prize. Everything else was a means to that end. That model is now breaking down in ways that go beyond the usual search algorithm updates, and the businesses that are still measuring their digital marketing performance solely by keyword positions are at risk of misreading what is actually happening to their visibility.

The argument that recognition matters more than rankings is not a new one, but it has moved from theoretical to genuinely practical in 2026. AI systems are now doing much of the searching on behalf of users, assembling answers from multiple sources without users clicking through to individual sites. The question of where you rank in a list of ten blue links is becoming less relevant than whether your brand appears at all in the answers that AI systems generate.

Why rankings are a less reliable signal than they used to be

The mechanism by which rankings produced value was straightforward: rank well, appear near the top of the results page, get clicked. That chain of causation is weakening at multiple points. AI Overviews now absorb a significant proportion of queries that previously generated organic clicks. Zero-click search, where users get what they need without visiting any website, is no longer a niche concern. It has become the default for a growing category of queries.

At the same time, the buying journey for most products and services has become more fragmented. Someone considering a dental procedure, a culinary course or a care management platform might start with an AI-powered query, move through a Reddit thread or a YouTube comparison, check a review platform, and only then arrive at a branded search. The keyword at any single point in that journey is almost beside the point. What matters is whether the brand shows up meaningfully across the full arc of that journey, not just at the moment someone is ready to convert.

Rankings still matter. A page that ranks well organically is also more likely to be cited by AI systems, more likely to receive referral traffic from other sources, and more likely to appear in the kind of third-party contexts that build recognition over time. The point is not that ranking is irrelevant but that ranking is now a means to recognition, not an end in itself.

What recognition actually means in practice

Recognition, in the SEO context, means that your brand appears in meaningful contexts across the web beyond your own domain. It means you are cited when people write about your sector. It means AI systems draw on your content when assembling answers to relevant queries. It means your entity, the brand as a clearly defined and verifiable presence, is understood and trusted by the systems that shape modern search.

This shifts the emphasis of SEO work in some important ways. A single high-quality mention in a respected publication or industry resource is worth considerably more than fifty low-quality directory listings. Being cited accurately and consistently across multiple contexts, including forums, review platforms, sector publications and AI-generated content, builds the kind of signal that recognition-based SEO is trying to accumulate.

It also changes what you measure. Alongside keyword rankings and organic traffic, the metrics that tell you whether recognition is compounding into something commercially meaningful include unlinked brand mentions, referral traffic from third-party sources, direct traffic growth, and the frequency with which your brand appears in AI-generated answers for relevant queries. These are harder to track than a ranking report, but they reflect what is actually happening to your visibility more accurately.

Google Search Console has just made this more measurable

The timing of this shift is notable. Google announced at the start of June that Search Console is introducing AI performance reports: data showing how your content is appearing in AI-generated search features, alongside new controls that allow site owners to restrict or permit their content from being used in AI responses. This is a significant development. It means that AI visibility, which has been difficult to measure directly, is now becoming a reportable metric within the tools most marketing teams already use.

This builds on the tooling landscape we covered recently when looking at the platforms worth using for AEO work. The addition of native AI reporting in Search Console closes one of the most significant gaps in the measurement stack, and it means the argument for taking AI visibility seriously now comes with data to support it rather than just directional signals.

What this means for content and SEO strategy

The practical implications of a recognition-first approach are not dramatically different from what good SEO has always required. The fundamentals still hold. The shift is in emphasis and in how you evaluate whether the work is producing results.

• Quality of context over volume. A mention in a respected trade publication, a citation in an AI-generated answer, or a detailed review on a trusted platform does more for brand recognition than a high volume of thin directory entries. The emphasis should be on creating content and building relationships that generate substantive, contextually relevant references to your brand.
• Entity clarity. AI systems and search engines need to understand what your brand is, what it does, and how it relates to the topics you want to be known for. Structured data, consistent NAP information, clear about and contact pages, and a coherent presence across multiple authoritative sources all contribute to entity clarity. This is not glamorous work, but it underpins everything else.
• Content that answers specific questions. The content that AI systems draw from and that earns citations and mentions tends to be content that answers a specific question clearly and completely. Generic, broad content that covers a topic without taking a clear position or providing a definitive answer is increasingly unlikely to appear in AI-generated results.
• Branded intent as a commercial signal. When someone searches for your brand by name, that is recognition in action. A branded search that lands on a generic or poorly structured homepage is a wasted signal. Every branded intent visit should arrive at a page, answer or experience that closes the gap between recognition and conversion.

The framing of recognition over rankings is ultimately about accepting that the metric you have been optimising for is no longer the one that most reliably predicts commercial outcomes. Rankings are a proxy for visibility. Visibility is a proxy for recognition. Recognition is what actually drives the journey that leads to revenue.

That does not mean abandoning the work of ranking well. It means doing that work with a clearer understanding of what it is trying to achieve. A page that ranks well and is well-structured, authoritative and specific in what it answers is also a page that gets cited, shared, referenced by AI systems and remembered by people who encounter it. The tactics are largely the same. The goal is broader.

For businesses still measuring their digital marketing performance primarily by a monthly keyword ranking report, now is a good time to extend that view. Rankings tell you one thing about your position in one channel at one moment in time. Recognition tells you whether you are building something that compounds. In 2026, the latter is the one that matters more.

OpenAI have begun the rollout process of ads across its AI generative engine, ChatGPT. Users in the UK were prompted to select whether they wanted tailored ads based on the collected data from previous prompts or generic ones.

How can brands secure ad space on ChatGPT?

The sign-up process for marketing campaign ads on ChatGPT prompts users to create an account and provide basic business details.  Then, once the account is live, you’ll need to follow this process to upload your campaign:

1. Create a campaign

Setting up a campaign is done within ChatGPT’s ads manager. This provides controls around goals, which are the desired reach and clicks. Once set, you’ll then input the campaign name, your budget, the start and end dates, as well as toggle the targeting settings to your preference.

• Create ad groups

Ad groups are designed to provide conversion context hints. Allowing you to position campaigns by contextual relevance rather than utilising keywords like Google Ads would.

Within the ad groups, there are additional controls on bidding settings and in certain cases, audience parameters are also available.

• Start producing your ads

Unlike a Google, Meta or LinkedIn ad campaign, the actual result achieved greatly differs. Ad managers need to paste in a headline, description and the landing page URL.

The key difference is the asset; while a traditional style campaign image can be used, it’s often better to use a high-resolution logo or photograph, as the display size is modest and will need to be legible to users.

• Upload campaigns in clusters

ChatGPT is fitted with capabilities to support multiple campaign uploads.

The workflow is:

• Download your campaigns template.
• Fill in all of your campaign, ad group, and ad information.
• Upload the completed file through Ads Manager

What do the ads on ChatGPT look like?

Each campaign is displayed just above the text box, positioned below any search results.

How will UK regulation impact advertising on ChatGPT?

There are a number of regulations that will impact both the user experience and campaign managers. EU regulations and policies stipulate:

Consent requirements in the EU mean users must provide consent before their personal data can be used to personalise advertising. If users choose not to opt in, advertisers may need to rely on contextual targeting or generic advertisements instead.

Restrictions on the types of campaigns allowed. EU regulations place significant restrictions on the use of sensitive personal data for advertising, profiling of children, and certain forms of political advertising. As a result, advertisers face tighter controls over how campaigns are targeted and delivered compared with many non-EU markets.

As ChatGPT continues to evolve from a conversational AI platform into an advertising channel, brands are being presented with a new opportunity to reach users in highly contextual environments. While the platform’s advertising capabilities are still developing, its emphasis on conversational relevance rather than traditional keyword targeting could reshape how marketers approach campaign planning. However, with increasing regulatory scrutiny around privacy, personalisation and AI-driven advertising, businesses will need to balance innovation with compliance as they explore this emerging marketing channel.

The digital advertising landscape is experiencing a foundational shift. OpenAI has officially transitioned its conversational AI advertising from a quiet pilot into a fully-fledged media channel. With a self-serve Ads Manager, cost-per-click (CPC) bidding, and advanced tracking pixels now live, conversational marketing is moving from an experimental tool into a core acquisition strategy. For forward-thinking brands, understanding how to navigate this new ecosystem is no longer optional.

Understanding the Conversational Ad Engine

Unlike traditional search engines that rely heavily on keyword bidding, ChatGPT ads are triggered by contextual relevance and user intent within a live chat session. Sponsored cards appear cleanly beneath the AI’s organic response, ensuring that the ad does not compromise the core user experience. This means brands are purchasing premium proximity to highly engaged, intent-rich decision moments. Furthermore, if users opt into personalisation, the system can safely leverage previous chat history and session memory to match the most relevant ad to the consumer.

Strict Guardrails and Product Catalogue Demands

OpenAI has established non-negotiable parameters around data privacy and brand safety. Advertisers never receive raw chat logs, names, or precise locations; instead, performance is delivered via non-identifying aggregate data. Additionally, ads are strictly prohibited in sensitive verticals like healthcare, politics, and financial services. For e-commerce retailers utilising the new automated product feed ads, entry requires a rigorous compliance check. Brands must submit a flawless 100-product sample feed evaluated for data completeness and high creative standards before their full catalogue is accepted.

Preparing Your Brand for AI-First Marketing

To capitalise on this rolling expansion, marketing teams must optimise their assets for conversational environments rather than keyword density. Ad copy should adopt a calm, confident register that echoes the natural phrasing of user queries. Because the system utilises session memory, establishing a strong organic presence through Answer Engine Optimisation (AEO) is vital. Ensuring your brand is consistently cited in early research stages will organically compound your relevance when the ad auction triggers later in the buyer’s journey.

Everyone’s currently talking about the advantages of AI, how it can be a useful tool to improve workflow, making tasks that would have taken months take days, tasks that would have taken days take hours, but many people aren’t focusing on what tasks we should not be using AI to automate. In a world of automation, the human touch is now more important than ever.

Keyword Research

This one seems like it doesn’t make sense. Surely using AI for keyword research is great, right? Well, yes to a certain extent. AI can be incredibly useful for going through your site and picking out key topics, keyword groups and helping you create a framework for your keyword research, while making sure there are no gaps in your keyword strategy.

However, when you’re looking at which keywords to focus on to build out content, this is where it gets a little bit more tricky. For example, for a business that sells a service or product, you understand which keywords are going to generate more revenue and how they have intrinsically more value to your business than some other keywords that may have more search volume and a lower CPC that AI is telling you to focus on. Make sure you use AI to optimise but don’t let it dictate your keyword strategy. You need to take into account factors such as conversion and revenue when making these decisions.

Client Reporting

Similar to keyword research, of course we aren’t saying AI isn’t helpful at all when reporting to clients, but it’s not the be-all and end-all. AI can be used to help you create your physical report incorporating data, giving suggestions on different slides and angles you can tie into your reporting, helping you formulate talking points. All good stuff. But something AI can’t replace is client communication.

A lot of digital marketing is highly specialised and can get confusing quickly for clients who aren’t familiar with it. One of the skills of a marketer is to be able to convey these complex concepts to their clients in a presentable and succinct manner so that they can understand the value of your contribution and how important it is to their business.

By all means use AI to help you build out your client reports, but clients need interaction in order to be able to digest and understand a lot of the data that they’re seeing, and at the minute that’s still where the human element comes in.

Content Writing

This is one of the biggies. Over 50% of newly published articles and nearly 75% of newly created web pages now include AI-generated content. The problem that businesses face when doing this is they lose their brand voice and identity, but also, AI is being fed content from the internet to train and learn. Which means unless people are using AI to inform their content deliberately and writing it themselves, then the content becomes generic and regurgitated, offering nothing new. This is exactly the type of content Google hates. It wants content that is fresh, original and gives a unique perspective and voice on a topic from an authoritative figure in the space; this is what you should be aiming for. Too much AI Slop on the internet is a problem for Google, and they are penalising people who are using it in the wrong way.

Making sure you know when and how to use AI is crucial to building a successful website. If you’re using AI incorrectly, your site can be penalised by Google and negatively affect your rankings, but use it correctly, and your site will benefit from a boost in workflow productivity and efficiency.

Nostalgia marketing is a key tactic used to tap into emotional and resonant memories from the past. When used effectively, it can bring feelings of joy or contentment; this familiarity that’s established helps to reinforce trust and authority.

What Can Make Nostalgia Marketing So Effective?

Creating feelings of nostalgia is a technique which taps into culture, emotion, identity, social connection and even moments of escapism. By creating a moment for viewers to reminisce, brands are able to effectively make the audience engage, which can help with their effort to strengthen emotional bonds and influence purchasing decisions.

Utilising nostalgic elements is particularly effective for prompting emotional engagement; it often helps brands stand out in oversaturated markets. People are more likely to engage with and invest in something which creates this kind of response.

When a campaign is able to successfully connect to existing memories, the recall of messaging, helping to forge trust. Rather than the viewer creating a new association, it is associated with memories consumers already have.

Familiarity often prompts people to discuss the past, which encourages viewers to share and engage with campaigns. This not only helps improve reach, but it also improves brand awareness and recognition. This type of engagement helps create social proof. Consumers engaging with it in this sense implicitly signal that it’s worth paying attention to.

When Doesn’t Nostalgia Marketing Work?

Whilst it can be powerful, this tactic isn’t automatically effective. This can happen when the nostalgic element overwhelms the messaging, isn’t aligned with the offering, or lacks relevance to the audience. For instance, what may be nostalgic for a millennial may not land at all for a Gen Z consumer.

The most common causes for nostalgia-based campaigns not working include:

• When the campaign feels forced
• Seeming inauthentic
• It conflicts with the brand’s position
• The nostalgia factor overshadows the product
• People’s unique experiences and responses
• Potentially overused or tired product campaigns

Key Examples of Successful Nostalgia-Based Marketing Campaigns

Some key examples of when it’s been done right include Argos’ “toys” campaign. McDonald’s adult Happy Meal product campaigns, along with Cadbury’s 200-year celebration of the brand.

‘There’s more to Argos than toys’

Argos’ latest campaign draws on nostalgia through clever visual references. Using everyday items like fridges and sofas in bold packaging reminiscent of children’s toy boxes, the campaign reminds people that Argos is more than just a place to buy toys.

For readers who grew up in the generation of catalogues, the throwback to getting toys from Argos is a fond memory. I too grew up circling the ideal toys for my Christmas list, so seeing this campaign puts a clever spin on how brands grow alongside their audience.

The campaign cleverly reminds passers-by that Argos stocks far more than what’s in the toy box, reinforcing the message that “there’s more to Argos”.

Cadbury’s Celebrated 200 Years of Business

Arguably, one of the best campaigns for its nostalgia factor was Cadbury’s 200-year celebration, which saw packaging revamped or, more fittingly, pulled back in time through the revival of its historic designs.

The TV advert produced alongside the campaign perfectly matches the nostalgic feel. It sets the scene at the advent of the Dairy Milk bar before transitioning into a present-day setting, showing that whilst times may have changed, consumer buying habits and emotional connections to the brand remain the same.

McDonald’s Adult Happy Meals

Whilst McDonald’s hasn’t explicitly marketed its adult meals as “Adult Happy Meals”, many of us who grew up pleading with our parents for a Happy Meal will recognise the same sense of excitement through its recent promotional releases.

Initially, it was the Grinch collaboration that sparked excitement. Customers could order a Grinch meal, featuring adult-sized products accompanied by a free pair of socks. This was then followed by the Friends x McDonald’s collaboration, where consumers were able to collect one of six figurines of the characters. Now, the excitement continues with the announcement of a new cup release for the FIFA World Cup.

The latest “Adult Happy Meal” taps directly into 2000s nostalgia through the return of the collectable Coca-Cola glasses, something that seemed to exist in every British household.

The campaign is particularly effective because it taps into the positive emotions attached to nostalgic purchasing experiences, reminding consumers of the excitement and familiarity associated with childhood treats and collectables.

Nostalgia is most effective when it supports a brand’s message rather than replacing it. While nostalgic campaigns can build emotional connections, trust, and engagement, they can fail when they feel inauthentic, target the wrong audience, or rely so heavily on the past that consumers lose sight of the product itself. The most successful campaigns use nostalgia as a bridge between meaningful memories and a compelling modern brand story.

If you run paid search campaigns, this week just got urgent. Google has begun deleting hourly, daily, and weekly reporting data older than 37 months, with the policy taking effect from 1 June 2026. This is what needs to be done over the coming days.

What’s Actually Changing and What Isn’t

It’s easy to panic, so let’s be precise. Granular reporting data, including hourly, daily, and weekly figures, will now only be retained for 37 months, while monthly, quarterly, and annual data remains accessible for 11 years. Once data passes its retention window, it will no longer be accessible through the Google Ads interface or APIs – meaning your dashboards, automated reports, and data warehouse pipelines could all be affected. If your agency holds years of campaign history for benchmarking or client reviews, that granular layer is now gone unless you already exported it.

Why This Hits Agencies the Hardest

For those of us managing multiple client accounts, the operational risk here is significant. Organisations running complex omnichannel reporting by blending data from multiple Google APIs need to audit their extraction workflows carefully to avoid serving clients incomplete performance dashboards. Think about seasonal trend analysis, day-of-week performance benchmarking, or long-term A/B test comparisons; all that granular intelligence becomes inaccessible without proactive data management.

Three Actions to Take This Week

Don’t wait for a client to ask why their historical chart has gaps. First, export all hourly, daily, and weekly data beyond 37 months immediately. Second, review any automated reporting workflows to confirm whether they store historical data independently or only query Google Ads on demand. The latter will now fail silently. Third, consider moving to a third-party data warehouse solution to ensure long-term retention sits outside Google’s control entirely.

Astro is not a content management system like WordPress, Wix or Shopify; however, it could be the new alternative. A content management system is defined by the ability of its users to create, manage, store and publish content. Astro doesn’t offer these features in the traditional sense, but it is a modern web framework that allows users to build fast, static HTML websites. This basically means that your website is created using code rather than a content management system; however, Astro lets you reuse layouts, components and templates to minimise the code and build large, fast websites that are optimised for SEO.

Where is WordPress faltering?

Why would you want to look for an alternative to WordPress, you may be wondering? While WordPress is the largest CMS on the market with some impressive features, including an extensive plug-in library and a large community, it also has its drawbacks as well. WordPress has a built-in editor and a theme that all come with their own code, but devs often install alternative themes or page builders to improve page build efficiency in WordPress. All these features can lead to page bloat as code is coming from the editor, the theme and the page builder, slowing down sites and negatively impacting SEO. 

How can Astro solve WordPress issues?

For issues with code bloat and site speed, Astro is dramatically better than WordPress. Astro will not only remove any of the additional page bloat issues that accompany WordPress, but you can also create reusable components to speed up your build process, known as islands. These islands allow users to save sections of code to re-use, which Astro will then take and turn into plain HTML, making the build much faster. This process helps devs to create a site that is SEO friendly, excelling in speed and core web vitals, which are both ranking factors for SEO. Below is a snapshot of some of the key features of Astro. Some other features include server-first rendering, which once again helps speed up sites for the end user and more

Where is Astro still behind WordPress?

The advantage WordPress still has over a platform like Astro, and it is a big one, is accessibility and ease of use for the masses. While for developers, Astro may be easy to use and update content, for non-technical editors or teams with lots of publishers without a background in development, it does not allow these users the flexibility to go in and edit the content.

There is a fix for the issue with Astro; however, it is compatible with a headless CMS. This basically means your code is integrated into a CMS that doesn’t have its own code and allows your publishers an admin panel to edit content.

Astro has both advantages and disadvantages of WordPress, but for users who are seriously thinking about alternatives to WordPress to improve site speed on a bloated site, Astro is a really important alternative to consider.

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.