It often begins with a scroll. Something catches the eye and within minutes it’s in a cart. That familiar impulse has become the default mode of discovery for millions of consumers. But that’s not a revelation. What is changing – and fast – is how platforms are learning to anticipate those impulses before they even surface.
Platforms such as Meta, Google, TikTok, Snapchat and Spotify are no longer passive mirrors of consumer behaviour; they are microscopes that interpret why people want what they do – and what they will want next. That means every campaign is first evaluated by algorithms, AI assistants and other invisible gatekeepers before it reaches the human eye.
For marketers, the prize is real-time market intelligence: the ability to detect emerging preferences, test reactions instantly and predict demand patterns with greater clarity.
Winning in this environment blends systems-thinking with storytelling instinct. It starts with interoperable data across fragmented commerce, customer relationship management (CRM) and media stacks, then layers on AI to scale creativity and performance. Platforms are attempting to meet that need by unifying and activating first-party data; keeping signals fresh while proactively catching catalogue and event errors and turning best practices into actionable, account-level recommendations.
B2M: Marketing to machines
For marketers, this evolution isn’t just about better engagement; it’s about insight. The ability to detect emerging preferences, test reactions in real time and predict demand patterns offers a new kind of market intelligence.
Before any ad or campaign reaches the human eye, it is judged, filtered, and prioritised by machines. As Ahmad Numan, Director of Marketing and Corporate Communications, Ras Al Khaimah Economic Zone (RAKEZ), states in an opinion piece submitted to Campaign Middle East earlier this year, this is B2M: business-to-machine. Marketers need to understand each platform’s brain – a one-size-fits- all approach never worked; it won’t work now.
Numan says, “Algorithms, AI assistants and invisible gatekeepers decide what’s shown and what’s forgotten. And brands that understand this and design for it are already pulling ahead.”
He continues, “Marketers who win today are those who blend systems-thinking with storytelling instinct. You don’t need to code. You need to understand the ecosystem you’re trying to enter – and who guards the gates. Win the machine, reach the human. Lose the machine, and you remain invisible. Your move.”
Data integration at scale
While advertisers now have access to highly advanced event taxonomies and data, the real challenge lies in interpreting and operationalising them across fragmented ecosystems – where commerce, customer relationship management and media data often sit in silos.
Platforms such as Google, Meta, Snap and TikTok are equipping marketers with tools to address these challenges.
“Google helps marketers overcome the challenge by providing different tools to interpret, integrate and ensure interoperability of their data. Google Marketing Platform, with Google Analytics (GA4 and GA360) at its core, unifies advertising and analytics to provide a single source of truth for understanding customer behaviour. Google Cloud is also a powerful platform for data integration at scale,” says Aishi Lahiri, Director, Advertising Solutions – Google Middle East and North Africa.
Lahiri adds, “Brands can use BigQuery, a serverless data warehouse, to bring together their marketing data with their own first-party data – whether that is CRM, sales or offline data. Google Cloud’s architecture is designed to be open and flexible, allowing businesses to use Google Cloud alongside other cloud providers.”
Leaders also point to the stream of data behind every ad, cautioning that when that data is broken, outdated or disconnected from the ecosystem, even the best campaigns can stumble. Brands are often stuck manually patching catalogues and tracking errors, but smarter AI tools are beginning to take over the grunt work.
For example, Snap aims to empower advertisers to maintain accurate and up-to-date data by facilitating seamless integration between its systems and theirs.
Nicerine Sadouki, Head of Client Solutions, UAE at Snap Inc., says, “Our conversions application programming interface (CAPI) enables brands to transmit events such as purchases or sign-ups directly from their servers, ensuring that signals remain fresh and reliable. We also collaborate with mobile measurement partners (MMPs) to verify and integrate app data.”
Sadouki adds, “When combined with dynamic product ads (DPAs), this approach minimises the manual effort required to update catalogues, allowing brands to deliver the most relevant products to their audiences and achieve stronger direct response (DR) outcomes. Beyond integrations, our systems proactively detect errors – such as missing events or mismatched catalogues – and provide real-time feedback and automated syncing.”
AI-powered solutions for performance optimisation
TikTok’s generative AI suite of creative tools, such as Symphony, assists with brainstorming ideas, script optimisation and efficient scaling of production. It simplifies the ideation and creation process, saving time and enhancing effectiveness.
But, in a content-first world, speed and relevance are everything. Brands need tools that not only spark creativity but also drive performance optimisation.
For instance, TikTok’s AI-powered media solution Smart+ automates campaign optimisation, ensuring content reaches the most relevant audiences for maximum return.
Testing shows that 78 per cent of catalogue ads using Smart+ outperform those managed manually, and web campaigns achieve a 53 per cent boost in return on ad spend (ROAS). Symphony and Smart+ support marketing teams with the tools they need to create, optimise and scale content that delivers quickly and effectively.
Similarly, Meta offers AI-powered recommendations such as Opportunity Score to guide campaign decisions.
Anna Germanos, Group Director FMCG, Luxury, Retail & E-commerce (MEA) at Meta, says, “Meta helps brands bridge the gap between advanced tooling and implementation with intuitive, AI-powered solutions that make innovation accessible and actionable. Over time, we’ve heard feedback from advertisers that it can be hard to know where to find our best practices or to know which best practice is most relevant to their account.”
Germanos adds, “Tools such as Opportunity Score make it easier for advertisers or agencies to find the right performance recommendation personalised to their account and implement it without guesswork. Opportunity Score gives advertisers research-backed recommendations for campaign adjustments to help improve performance, including adopting advanced AI optimisation as well as new performance ad solutions.”
AI enters the creator chat – with caution
If algorithms define the pulse of ongoing trends, then creators have become the new curators of culture – the human layer that gives content a heartbeat. Predictive AI can map behaviours, but it is creators who shape them. Platforms are now using AI to support creator workflows, amplifying influence and filling gaps in the creative process, which in turn feeds back into predictive systems.
Google MENA’s Lahiri says, “YouTube creators’ authentic and trusted relationships with their audiences provide brands with an unmatched opportunity to drive influence and achieve real results. That’s why we’re continuing to evolve the suite of creator tools powered by BrandConnect to help marketers more easily find, engage and work with the perfect creator for their campaigns. These include partnership ads, which allow a brand to promote videos mentioning their products.”
At Google Marketing Live, the platform announced Creator Partnerships Hub currently available to select advertisers, which enables brands to put out a request for sponsored content broadly to creators.
“Creators Partnership hub will help brands discover new and relevant creators, to get more from their social strategy on YouTube,” Lahiri adds.
Spotify is also leaning into AI to support creator workflows and enable new forms of content that feed back into predictive systems.
“We’re hearing from artists and their teams that they are curious and interested in how AI can help their creative process – whether they are recording in a studio, using digital audio workstations (DAWs), recording acoustic or using electronic sounds, using autotune or pitch correction, using AI workflows, or anything else,” says Mark Abou Jaoude, Head of Music for MENAP, Spotify.
Some examples include Randy Travis, who lost his voice due to a stroke, being able to release new authorised music using AI trained on his pre-stroke vocals. Brenda Lee’s iconic Christmas song was translated into Spanish, expanding its reach to global audiences.
Musician Lauv leveraged AI to connect with Korean fans by releasing a Korean version of a new song in his own voice. The Beatles’ Now and Then used AI to finish a decades-old demo, which later won a Grammy. Singer/songwriter Vince used ChatGPT while producing Soda Pop, which cemented its place in people’s heads and the Billboard Hot 100.
Creators aren’t just fuelling or following algorithms – they’re working alongside AI to teach algorithms what culture will look like in the near future.
Conversely, by combining creator-driven content with AI-assisted tools, platforms are capturing signals that anticipate future trends, giving advertisers actionable insight into what audiences will engage with before it even becomes mainstream.
However, addressing the ‘concerning side of AI’, Spotify’s Jaoude says, “AI has the potential to exacerbate or accelerate many of the industry-wide problems that already exist – such as spam, fraud and deceptive content. These things have no place on Spotify. That’s why we’ve announced stronger impersonation protections, rolled out a new spam filter and introduced a new industry-supported system for disclosing when AI was used in a track to continue making Spotify a more transparent, fair and trustworthy platform for artists and listeners.”
He adds, “We’ve announced three new updates aimed at making Spotify a more transparent, fair and trustworthy platform for artists and listeners.
The first is a stronger protection against impersonation – including AI voice clones and profile ‘mismatches’ with clearer artist recourse. Secondly, a new music spam filter identifies and stops spammy uploads from being recommended – whether that’s mass duplicates, SEO-gamed content or ultra-short track abuse. Thirdly, support for an industry standard, developed through digital data exchange (DDEX), discloses when AI was used to create music.”
AI-driven measurement – the long and the short
Even with the best creators, brands need smarter automation to ensure their content drives meaningful results, rather than over-amplifying short-term fads.
For several platforms, AI-driven optimisation has become part and parcel of how they ensure that performance is tied to business objectives rather than only virality.
For instance, Performance Max uses Google AI to optimise bids and placements across all its channels, including YouTube.
The placements and bids are based on the conversion goals the advertiser defines.
“Brands only need to provide the budget, business objectives and creative assets. The AI then works to find the most valuable customers to achieve the conversion goals, rather than simply maximising clicks or impressions on a trending topic,” Lahiri explains.
Google also rolled out AI Max in beta to advertisers globally earlier this year, which is a suite of creative and targeting enhancements for Google AI Search campaigns.
AI Max helps boost conversions and find new customers by using features such as search term matching to discover more high-performing queries, asset optimisation to generate ad copy, and final URL expansion to direct users to the most relevant pages on a website.
“Data already shows that advertisers that activate AI Max in search campaigns will typically see 14 per cent more conversions or conversion value at a similar cost per action (CPA)/ROAS,” Lahiri says.
Similarly, Snap’s measurement tools provide brands with a transparent connection between their advertising investments and the resulting outcomes.
Through CAPI, integrations with MMPs, and comprehensive reporting, advertisers can track how campaigns contribute to key metrics such as purchases, sign-ups, CPA and ROAS.
“Clarity facilitates swift budget reallocation toward the most effective strategies. For senior executives, trust hinges on transparency and consistency across platforms.
We are committed to enhancing these areas, allowing leaders to make the most informed and confident decisions,” Sadouki adds.
For years, marketers have tracked clicks, views, and impressions – but those numbers rarely tell the full story. The real question for chief experience officers (CXOs) today isn’t how many people saw an ad, but how much value it created.
As platforms evolve their measurement tools, the focus is shifting from surface-level metrics to hard business outcomes: profit, growth, and long-term loyalty.
Meta’s Germanos says, “Some conversions are more valuable than others, and marketers want to focus on conversions that generate the specific business results they care about, whether that is maximising profit, driving subscriptions that won’t churn, or reaching a certain demographic. For the advertisers who measure their performance based on incrementality experiments, we have recently completed the global rollout of Incremental Attribution, which is the only product in the market that optimises for and reports on incremental conversions in real time.
Advertisers who tested incremental attribution saw an average 46 per cent increase in incremental conversions compared to their business-as-usual campaigns.”
That said, CXOs need to also see the true return on their ad spend by measuring total sales – both online and offline – by capturing the full value driven by their digital investments.
Meta is solving this through its omnichannel ads, which Germanos says “are an optimisation solution that enables advertisers with existing omnichannel capabilities and a Conversions API for offline integration.
It provides the ability to safely send offline customer conversion information from the advertiser’s server to Meta’s server – to optimise the objective of a single campaign for both online and in-store sales.”
She adds, “The format is proving to deliver strong results – Foot Locker Middle East achieved a 15.2 times higher ROAS for omnichannel purchases in the UAE.”
However, positive outcomes aren’t only performance-orientated anymore. In the ongoing brand versus performance debate, measurement also encompasses long-term metrics.
This is why Google also offers measurement uplift tools such as Brand Lift, Search Lift and Conversion Lift to understand the causal impact of ads on users’ behaviours, not just views or clicks.
Lahiri explains, “These solutions measure the direct correlation between ad exposure and a user’s likelihood to search for the brand, as well as their propensity to convert.
This allows advertisers to quantify the true impact of advertising beyond just clicks and impressions, optimising for long-term brand growth and sales, with recent AI-powered updates enhancing accessibility and accuracy for a privacy-focused future.”
The need of the hour is to pair creator authenticity with machine-scale tooling. Marketers must lean into AI to amplify trusted voices and signal quality so that predictive systems can learn from what truly resonates, not just what trends.
Ultimately, B2M is validated in measurement.
Marketers need to lean into tools that align bids and placements with defined conversion goals, optimise for incremental outcomes in real time, and deliver brand lift in a way that moves beyond surface metrics to tangible profit and long-term brand loyalty.
