Cracking the Attribution Code: Marketing Measurement in 2026

Stop chasing the ghost of the click. Learn how to navigate the zero-click world of 2026 by mastering visibility as ROI, always-on incrementality, and Generative Engine Optimisation (GEO) to capture high quality leads.

Have you ever wondered if the data on your dashboard is lying to you? In my recent conversations with business leaders, the anxiety is real: organic traffic is cratering, while AI-driven signals are quietly surging.

For years, we treated the click as a sacred signal. A click meant interest, intent, and the comforting illusion that we were winning. But as we move into 2026, that tidy reality has shattered.

We are now living in a zero-click world. Nearly 60% of all searches now end without a single click to a website because AI engines provide answers directly on the search results page. This shift has turned our traditional attribution models into relics of a simpler time. We can no longer track the full customer journey with pixels alone.

This is what I call digital marketing’s dark matter: it is valuable, it is everywhere, and it is almost entirely untraceable. To survive, we must embrace intelligent uncertainty.

1. Visibility is the new ROI

Is your brand invisible if no one clicks on your website? This is the paradox of the AI funnel: while volume is plummeting, quality is skyrocketing. Clicks are falling, but brand impressions in AI Overviews are soaring by 49%.

AI-sourced visitors stay 4.1 times longer and deliver a 67% higher lifetime value than traditional search visitors. This happens because conversational interfaces act as filters. By the time a user finally clicks, they are not just browsing, they are deciding.

The Shift: Organic CTR has dropped from 15% in 2023 to just 8% in 2026.
The New KPI: Track branded search volume and share of voice in AI answers.
The Goal: If more people look for you by name, your invisible influence is working

2. Incrementality is the only truth

Are you paying for customers who would have bought from you anyway? This is the dirty secret of performance marketing. Last-click attribution often credits your ads for users already on a path to convert, inflating your ROI while masking wasted spend. In 2026, the only way to defend your budget in the boardroom is through incrementality.

Incrementality is not a measurement question; it is a systems question. It is about isolating the true lift that media creates. This requires a shift from tactics to infrastructure, where you run tests mid-campaign and optimise weekly.

Establish Baselines: Use holdout groups and geo-tests to find your true organic floor.
Parallel Systems: Run incrementality alongside old reports for one quarter to build trust.
Scale Gradually: Follow the 10% rule. Increase budgets gradually and validate every move with clean data.

3. GEO is the new SEO

In 2026, search engines are not just indexing your pages; they are learning from them. Generative Engine Optimisation (GEO) is about making your content machine-readable. If you are not found, you are not cited.

You are no longer just writing for people; you are writing to be part of the data AI learns from. Your goal is to become the trusted entity that the AI chooses to reference.

Optimise for Extraction: Use clear answer blocks of 40 to 60 words.
Entity Recognition: Implement Schema markup to boost your citation chances by 36%.
**E-E-A-T (Experience-Expertise-Authority-Trustworthiness)**: Use named experts with established authority to increase trust and citation probability.

Final Thoughts: Are you ready for the invisible hand to rewrite your rules?

Attribution in the AI age is no longer about the vanity of perfect tracking. It is about embracing intelligent uncertainty. The winners of 2026 will not be those with the prettiest dashboards.

The spoils will go to the marketers who build for citability, optimise for context, and ruthlessly value quality over volume. We must move faster from reporting what happened to understanding why it matters. The click as we knew it is gone, but the opportunity remains massive for those willing to adapt.

It is time to stop looking in the rearview mirror and start guiding the next move. If you are ready to scale with structure and navigate this new dark matter together, let’s talk.

🫶🏻 Thanks for reading till the end.

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From Google to TikTok: Social Search Marketing in 2026

Discover how social search is replacing Google as the new discovery engine in 2026. Learn why TikTok, AI, AR, and S-SEO are redefining consumer intent, brand visibility, and the future of digital marketing.

A few years ago, my Saturday morning ritual was simple.

Coffee, injury reports, and a dozen Google searches to optimise my Fantasy Premier League lineup. Today, none of that involves Google. Instead, I’m scrolling through TikTok for last-minute injury whispers, wildcard hacks, and highest differential captain picks. Not because I’m trying to be cool, but because the best answers aren’t on search engines anymore. They’re on social feeds.

That tiny shift in my routine mirrors a massive shift in global consumer behaviour. Search isn’t dying; it’s relocating. Discovery, intent, and decision-making are no longer triggered by static blue links. They’re being shaped by dynamic short-form videos built by creators and algorithms that learn faster than we do.

This is the rise of social search. And in 2026, it’s no longer a sideshow. It’s the new operating system for consumer discovery, powering a global commerce engine on track to reach almost three trillion dollars.

1. The Great Discovery Migration: Why Search Moved from Google to Social

For years, we treated Google as the front door to the internet. Today, that door is shifting, and most brands haven’t noticed they’re standing in the wrong hallway.

1.1 The economic displacement

The data is blunt. 82% of consumers now use social platforms for product discovery**, with Gen Z leading the shift at 76%. Social commerce in the US is marching toward $150B, while global projections hit $2.9T by 2026. This isn’t a trend curve. It’s a tectonic plate moving under every marketer’s feet.

And here’s the uncomfortable truth: while consumers migrate to TikTok and Instagram for answers, many brands are still optimising like it’s 2015. They’re building for search engines while their customers are discovering through creators, comments, and chaotic-good algorithm magic.

1.2 Intent isn’t just typed anymore

On TikTok, intent is a behaviour, not a query. It shows up in the micro-moments: how long you hover, what you rewind, what you save at 2 AM. These signals whisper more about interest than any typed keyword ever could. Short-form platforms have become intent-discovery engines that don’t wait for you to ask a question; they predict the question before you know you have one.

1.3 What this means for brands

If your brand only appears when someone types into Google, you’re already behind. In 2026, visibility lives in the scroll. If your content doesn’t appear when someone laughs, pauses, shares, or stops mid-swipe, you don’t exist. The algorithm doesn’t care about your domain authority. It cares about whether someone watched your video twice.

2. S-SEO: Social Search Optimisation and the Rise of the Three-Layer Index

For two decades, SEO revolved around one thing: text. Keywords, tags, metadata. In 2026, the universe has expanded. Social search now requires a three-layer indexing strategy that mirrors how platforms actually understand content.

2.1 Layer 1: Textual Signals (Captions, Keywords, Hashtags)

Think of this as the foundation. Captions need natural-language long-tail keywords. Hashtags should stay tight and relevant, ideally three to five. No hashtag stuffing. No keyword salad. Write for humans first, algorithms second.

2.2 Layer 2: Visual Signals (On-screen text)

On-screen text is your new title tag. TikTok and Instagram don’t just show your subtitles. They read them. A clear phrase like “Best moisturiser for oily skin” on screen makes your content discoverable even before a user engages. It’s a scroll-stopper and an indexing cue rolled into one.

2.3 Layer 3: Auditory Signals (Spoken keywords)

Here’s the twist no one saw coming. With near-perfect AI transcription, spoken audio is now a search surface. If you say “budget-friendly running shoes” out loud, TikTok treats it like metadata. The algorithm hears you. Literally. Brands that don’t script spoken keywords into their content are leaving discoverability on the table.

2.4 Velocity Metrics: The New Ranking Factors

In the old world, backlinks built authority. In the new world, velocity builds relevance. Platforms elevate content using metrics that show immediate audience interest:

Watch time
Completion rate
Rewatches
Shares

The For You Page is the new Page One, and the only way in is through content that hooks in three seconds.

3. The Search Horizon: AI, AR, and Zero-Click Commerce

We aren’t just replacing Google. We’re outgrowing it. What’s emerging in 2026 is a search landscape powered by intelligence, personalisation, and frictionless commerce.

3.1 AI-driven hyper-personalisation

AI now orchestrates a dynamic experience for every user. Search results re-rank in real time. Product pages morph based on behaviour. Offers change depending on loyalty, price sensitivity, or previous interactions. This isn’t segmentation. It’s micro-personalisation at scale.

3.2 Visual search as the new discovery engine

TikTok Visual Search lets you find products by pointing your camera. No typing. No guessing. No Google. It’s a discovery without effort and intent without a query. A camera becomes the most intuitive search bar in the world.

3.3 AR as the new trust indicator

AR try-ons bridge the last gap between desire and decision. Want to see how the lipstick shade looks or whether the sneakers match your fit? Try them on instantly. One swipe later, you’re at checkout.

By 2026, discovery, research, and purchase no longer live in separate stages. They happen in one continuous motion, inside one app, powered by one algorithm that knows what you want before you articulate it.

Final Thoughts: The Search Singularity Has Arrived

We’ve crossed a threshold. Search is no longer a destination. It’s a behaviour woven into every swipe, pause, and rewatch.

What started as a small shift in how I choose my Fantasy Premier League captains has become a global reordering of how consumers discover, evaluate, and buy.

To stay visible in 2026, three strategic imperatives matter more than anything else.

1. Master S-SEO

Engineer every piece of content for layered indexability. Text, visuals, and spoken audio must work together as one search-optimised engine. If it isn’t indexable, it isn’t findable.

2. Prioritise authenticity

Trust has become the algorithm. UGC, detailed reviews, and micro-influencers don’t just make your brand relatable. They make it rank.

3. Profitable attention

Traffic is a vanity metric. The real KPI is attention that behaves with intent: the rewatch, the save, the share, the click that leads to action. Attention that compounds is the new form of ROI.

If Google was the library of the internet, TikTok is the living marketplace. The future of search isn’t typed. It’s scrolled.

🫶🏻 Thanks for reading till the end.

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Attribution in the AI Age: Tracking the Invisible Hand

Discover why attribution is breaking in the AI era & how marketers can measure invisible influence from ChatGPT, Perplexity, & Google’s AI Overviews through new frameworks for the zero-click world.

Since last year, one of the things companies I’ve met always lament to me is that their organic search has been on a steady decline.

No matter how much content they churn out, how often they tweak meta descriptions, or how big their SEO budget gets, nothing seems to move the needle.

The game has changed.

While marketers fixate on cookie deprecation and privacy laws, a far more disruptive force has quietly rewritten the rules of digital discovery. Generative AI isn’t just another channel; it’s a black box that’s swallowing traffic, out-converting search, and leaving attribution models gasping for oxygen.

Here’s the uncomfortable truth:

🔹 80% of consumers now rely on zero-click AI results for 40% of their searches.

🔹 When Google’s AI Overviews appear, organic CTRs collapse from 15% to just 8%.

🔹 Some industries already see 5–10% of top-funnel traffic originating from LLMs, and that’s just the visible part of the iceberg.

🔹 Even more startling: AI-driven traffic converts at 1.66% vs. search’s 0.15%. ChatGPT users? 16% conversion, versus Google’s 1.8%.

These aren’t rounding errors. They are seismic shifts in how discovery, intent, and influence work.

So, how do we measure what we can’t see?

How do we attribute revenue to conversational interfaces that strip away referrer data?

And how do we optimise for platforms where “ranking” doesn’t even exist?

1. The New Search Reality and the Zero-Click Apocalypse

Traditional search was tidy: query → click → website → conversion.

Linear. Measurable. Controllable.

The AI age shattered that pathway into a thousand probabilistic fragments.

Nearly 60% of all searches now end without a single click. AI Overviews make impressions soar 49% while clicks fall 30%. For publishers, SaaS firms, and education sites, that’s an existential threat when the top-of-funnel collapses, so does awareness.

And here’s the kicker: only 1% of users who see an AI Overview actually click a cited link.

Your content could power an AI’s answer, create user value, and build brand authority—and you’d never know it. No traffic. No pixel. No attribution signal.

Welcome to digital marketing’s dark matter: valuable, invisible, and untraceable.

2. The Quality Paradox

But buried in the chaos is a twist.

While volume plummets, quality skyrockets.

AI-sourced visitors view 3.2× more pages, stay 4.1× longer, and deliver 67% higher lifetime value. They refund less, refer more, and convert at rates traditional search would envy.

Why?

Because conversational interfaces act as pre-qualification filters.

Before clicking, users have refined their needs through multi-turn dialogue and received contextual recommendations.

When they finally visit your site, they’re not browsing, they’re deciding.

It’s the paradox of the AI funnel: fewer clicks, higher intent, zero visibility.

3. The Attribution Breakdown

Attribution in the AI age feels oddly familiar. It’s Mad Men-era advertising with modern dashboards. We know it works; we just can’t prove how.

Three problems define the crisis:

No visibility into rankings. You can’t “rank check” a ChatGPT answer. There’s no Search Console for Perplexity (yet!).
Inconsistent linking behaviour. Some LLMs link; others paraphrase without attribution.
Broken referrer data. AI clicks often show up as “direct” or “organic,” burying true influence under digital noise.

We’re not facing a measurement problem.

We’re facing a visibility problem.

4. How do we Build a Playbook for the Invisible?

Here’s how modern marketers can turn fog into signal.

1. Track Proactively with Smart UTMs.

Add UTM parameters to community posts, documentation, and partner content. Anywhere LLMs crawl.

2. Build Custom LLM Segments in GA4.

Create filters for domains like chat.openai.com, perplexity.ai, and gemini.google.com.

Compare engagement metrics versus organic and paid. The deltas will reveal where AI traffic hides.

3. Embrace Web-to-App Attribution.

Use unified links (like Appflyer’s OneLink) to track users moving from AI chats to mobile apps.

4. Speak the Language of Machines.

Structured data (Schema.org) boosts your chance of being cited by 36%.

Think FAQ, HowTo, Product, and Organisation markup. These are clear signals for LLMs.

5. Optimise for Generative Engines (GEO).

Write for extraction, not just humans.

Use question-based headings, bullet points, expert quotes, and concise stats. Make your content quotable by AI.

6. Accept Probabilistic Measurement.

Track indirect signals like brand search volume, direct traffic spikes, and post-launch cohort lifts.

Perfect attribution is dead. Intelligent triangulation is the new north star.

5. So What’s The AI-First Attribution Framework?

A modern model layers direct data with probabilistic signals:

Direct Measurement – UTM links, GA4 segments, structured data
Probabilistic Models – Markov chains, Shapley values, data-driven attribution
Indirect Signals – Brand searches, direct traffic patterns, surveys
Qualitative Intelligence – LLM audits, customer interviews, sales feedback

Together, these layers form a composite map of influence that is ****imperfect but actionable.

Final Thoughts: The Bottom Line

Attribution in the AI age isn’t about perfect tracking. It’s about embracing intelligent uncertainty.

The winners won’t be those with the prettiest dashboards.

They’ll be the ones who build for citability, optimise for context, and value quality over volume.

LLMs are now the new gateways to content, products, and apps. The visibility is murky, the attribution broken, and the opportunity massive.

Five years from now, we’ll remember 2025 as the year search split in two:

One world we could measure with precision,

and another that demanded faith, experimentation, and adaptability.

The question isn’t whether you’ll adapt. It’s whether you’ll adapt fast enough.

🫶🏻 Thanks for reading till the end.

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In the Age of AI, Growth Marketers Must Become Storytellers

In a world where AI can write, analyse, and optimise better than humans, storytelling has become the last true differentiator for growth marketers. Discover why the future of marketing belongs to those who can turn data into emotion, metrics into meaning, and campaigns into connection.

I’ve got to be honest. I was doomscrolling on TikTok when I stumbled on a scene from a Steve Jobs biopic. In it, Jobs likens himself to a conductor. Aligning the orchestra of Apple’s technology so that it resonates emotionally with users. Here’s the clip. He wasn’t talking about marketing, but he might as well have been.

Because somewhere between the violin of creativity and the percussion of data, we growth marketers lost the music.

For the past decade, we’ve been optimising the life out of marketing. We turned creativity into calculus: A/B testing, bid optimisation, segmentation, attribution models. Growth marketing became a science experiment where “success” meant higher CTRs and lower CPAs. We traded instinct for dashboards and storyboards for spreadsheets.

And now, AI can do all of that better than us. It can write copy, analyse data, and optimise campaigns while we sleep.

So here’s the uncomfortable question: if AI can do everything we do, then what’s left for us?

The answer is the one thing machines can’t touch: the asymptote of human storytelling.

Setting the Stage: The Performance Paradox

When Optimisation Becomes Homogenisation

Growth marketing earned its stripes through ruthless efficiency: track, measure, optimise, and repeat. For years, it worked brilliantly until everyone started doing it.

Now, every brand looks like a clone of the next. The same keywords. The same templates. The same “We’re different” headlines were written by ten thousand marketers using the same AI prompt. We’ve built a world where performance marketing performs but doesn’t inspire.

The Dirty Secret of Performance Marketing

Here’s the thing no one likes to admit: performance marketing only works when you have something worth performing with.

You can’t A/B test your way to brand love.

You can’t retarget your way to loyalty.

And you definitely can’t optimise a story that never existed in the first place.

We’ve just been running faster on a treadmill, forgetting that efficiency without meaning just gets you nowhere, faster.

The Data Doesn’t Lie (But It Can’t Feel Either)

The irony? The numbers prove that numbers alone aren’t enough (pun intended).

Storytelling marketing has grown 46% in the last five years.
It drives a 30% increase in conversions.
People are 22× more likely to remember a story than a statistic.
Emotionally connected customers deliver a 306% higher lifetime value.

The ROI of emotion is real and irreplaceable.

1. AI Raises the Floor, Storytelling Sets the Ceiling

Jason Ing, CMO of Typeface, put it perfectly: “AI raises the floor. Storytelling sets the ceiling.”

AI has democratised creation, but in doing so, it’s flooded the market with sameness. Everyone can generate a LinkedIn post, write an ad, or draft a blog in seconds. The result? An ocean of content and a drought of connection.

Even OpenAI, the company that could automate its own marketing, chose to film its first brand ad on 35mm film, using real actors, a real director, and real emotion. Because even the architects of artificial intelligence understand that emotion cannot be synthesised.

In a world where 94% of consumers worry about misinformation and 86% say authenticity drives brand choice, the paradox is clear:

AI abundance has created an authenticity drought.

2. The Algorithms Can’t Feel What We Feel

Author Ken Liu once said, “You are constructing artefacts out of symbols.”

That’s what data does. It translates reality into representation. But unlike machines, humans don’t just read symbols, we feel them.

Data can simulate language, but not meaning. AI can produce sentences, but not sentiment. It can write content, but not a connection.

A story isn’t an information packet; it’s a mirror held up to the soul.

What makes stories powerful isn’t logic, it’s liminality: the space between words where emotion lives, where we find resonance, nostalgia, and hope.

3. From Data to Dragons

Scott Galloway once said, “Storytelling isn’t decoration, it’s the strategy.” And he’s right. The companies that master narrative don’t just gain market share, they gain mindshare.

Consider these examples:

ASICS blended AI-powered personalisation with authentic storytelling—and had one of its best-performing years ever.
Travel Oregon’s “Only Slightly Exaggerated” campaign turned tourism into emotion, generating over $50M in economic impact.
Airbnb didn’t sell rooms; it sold belonging—a narrative that built a global movement.
Dos Equis didn’t just push beer; it introduced The Most Interesting Man in the World, and grew sales 26%.

Seth Godin’s old truth still applies: “People don’t buy products. They buy stories that make them feel something.”

In other words: data convinces, but stories convert.

4. The New Growth Marketing Stack

Tomorrow’s growth marketer must be bilingual. Fluent in both data and drama.

Data gives you efficiency: analytics, automation, attribution.
Drama gives you empathy: narrative, character, emotion.

In this new partnership:

AI handles at scale, the pattern recognition, automation, and distribution.
Humans handle the soul, providing context, meaning, and emotional intelligence.

Personalisation is easy. Personal meaning is hard.

5. Building the Narrative Muscle

The most in-demand marketing skills for 2025 aren’t technical, they’re human.

Creativity. Communication. Storytelling.

Your new role as a growth marketer isn’t just to analyse metrics, it’s to translate them into meaning.

Start here:

Define your origin story. Why does your brand exist beyond profit?
Make the customer the hero. Your product is the tool that helps them transform.
Use the three-act structure. Setup. Conflict. Resolution.
Be authentic. 64% of consumers crave emotional connection. Don’t fake it.
Treat data like myth. Numbers tell you what. Stories tell you why.

Because in the age of AI, the growth marketers who win won’t just be analysts.

They’ll be architects of emotion.

Final Thoughts: The Asymptote Advantage

Jason Ing said it best: AI is an asymptote. It will get infinitely close to human storytelling, but it will never touch it. And that tiny gap, that sliver of imperfection, is your edge.

When every marketer has access to the same AI tools, prompts, and playbooks, your story becomes the ultimate differentiator.

Growth marketing and brand storytelling are no longer two disciplines. They’re two sides of the same coin.

Storytelling gives depth. Performance makes it scale. Together, they form the only strategy that still feels human in an algorithmic age.

So the question isn’t if AI will change marketing. It already has. The real question is: in five years, how will we be remembered?

As the generation that turned marketing into math?

Or the one that rediscovered its soul?

So let the machines optimise. You humanise.

Now, close your analytics tab. Open a blank page. And ask yourself, quietly but honestly:

“What story am I trying to tell?”

🫶🏻 Thanks for reading till the end.

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AI Adoption and the Rich-Poor Divide: An Ethical Dilemma

AI can be the great equaliser, or the ultimate divider. This thought-provoking read explores how AI adoption could bridge or widen the rich-poor gap, with global examples, a Singapore case study.

This week in my BCG Digital Transformation and Change Management course, our team tackled a hackathon-style project on Robotic Process Automation (RPA). In just 48 hours, we went from concept to a future vision of where RPA, supercharged by AI, transforms industries overnight.

While we celebrated the promise of fewer errors, faster processes, and more innovation, it pulled me back to a conversation at last week’s Future Forward roundtable on AI ethics. The question wasn’t whether AI would change the world. The real question was: who would it change it for?

AI is often pitched as the great equaliser, delivering world-class healthcare, education, and economic opportunity to anyone with a connection. But it could just as easily become a great divider, locking progress behind paywalls and bandwidth speeds.

Here’s the reality: one-third of the world still remains offline. Meanwhile, advanced economies and tech giants are accelerating at full throttle in AI deployment.

This post explores AI’s double-edged sword, how it could bridge or widen the rich-poor divide, through global examples and a closer look at Singapore.

1. The Promise of AI: Levelling the Playing Field

If AI is built for inclusion, it’s not just a technology; it’s a social equaliser. Done right, it can shrink the distance between the privileged and the underserved, making access to knowledge and opportunity less about geography and more about design.

Access to Critical Services

In South Asia, Google’s AI-powered flood forecasting sends early warnings to vulnerable villages, giving families hours, sometimes days, to get to safety. In rural clinics, AI diagnostic tools can detect diabetic blindness and tuberculosis from simple medical images with expert-level accuracy. No specialist on-site? No problem. AI becomes the doctor who never sleeps.

Personalised Education for All

In parts of Africa, platforms like Eneza Education use AI to deliver lessons via basic mobile phones, working offline and in local languages. It adapts practice questions to each learner’s level, giving rural students the same personalised feedback a wealthy city kid might get from a tutor.

Financial Inclusion & Economic Empowerment

In Latin America, AI-driven fintech apps are bringing banking to the unbanked, using alternative data to unlock loans for micro-entrepreneurs. In rural communities, AI farming tools connect small farmers to buyers and provide real-time weather or crop health insights—turning subsistence farming into a more sustainable business model.

Why It Matters

AI, when designed for inclusion, is the cost-cutter for expertise. It slices through economic and geographic barriers to deliver life-changing knowledge and services to those who’ve historically been locked out.

2. The Perils of AI: Supercharging Inequality

But here’s the shadow side: without guardrails, AI doesn’t just mirror inequality, it magnifies it.

Between-Country Gaps

Wealthy nations dominate AI R&D and investment. In 2023, the U.S. attracted $67B in private AI investment, over eight times more than China, which placed 2nd! Meanwhile, broadband in low-income countries can cost 30% of a monthly income, making access to AI-driven services a luxury.

Automation & Job Losses

In Bangladesh, the garment industry, which employs millions of low-income workers, faces up to 60% job losses by 2030 as AI-powered machines take over repetitive tasks. Globally, the IMF estimates 40% of jobs are AI-exposed. Advanced economies have safety nets and retraining programs. Developing nations often don’t.

Concentration of Power

The top AI firms (mostly in the U.S. and China) control vast datasets and computing power. The result? A monopoly on innovation where smaller nations and companies are left consuming, not creating, AI. As AI boosts efficiency, it might increase returns to capital more than labour. An example is when companies save on wage costs via automation, see higher margins, but workers see fewer job opportunities.

Bias & Exclusion

AI systems themselves can reflect and amplify societal biases, often to the detriment of marginalised groups. When Indiana automated welfare eligibility checks, over one million eligible applicants were wrongly denied. The lesson: if the training data is biased, the algorithm will be too, and it’s often the most vulnerable who get cut out first.

3. Case Study: Singapore – AI Leader, Ethical Crossroads

Singapore offers a microcosm of the AI inequality dilemma. We rank #1 globally in AI readiness (according to IMF) and have the fastest AI skill adoption rate in the world.

Inclusive Efforts

The government has heavily promoted digital transformation under its “Smart Nation” initiative, and Singapore’s workforce is considered the fastest in the world at adopting AI skills. Through SkillsFuture, Singapore offers subsidised training in everything from digital literacy to advanced AI, with extra support for older workers and people with disabilities.

On paper, Singapore is reaping AI’s rewards: automation is boosting productivity and innovation in sectors from manufacturing to logistics. However, the benefits and burdens of AI are unevenly distributed across different groups in Singapore, revealing ethical trade-offs even in a wealthy society.

The Other Side

As automation accelerates. The city-state’s lower-skilled income workers (including 1M migrant workers), who fill labour-intensive jobs in construction, cleaning, and domestic work, could be displaced without sufficient safety nets.

Singapore today is the second most robot-dense nation globally (730 industrial robots per 10,000 workers), and this automation has coincided with a steady decline in manufacturing employment even as output grows. There is a real risk that AI and robots will exacerbate socioeconomic divides, benefiting high-tech firms and skilled locals.

The ethical question: what responsibility does a nation have to the very workers who helped build it?

Key Takeaway

The Singaporean example underscores that even in a wealthy, tech-forward nation, deliberate policy is needed to ensure AI’s benefits are broadly shared and its disruptions are managed fairly.

4. The Balancing Act: How We Ensure AI Works for All

The dual nature of AI, as a potential equaliser and a possible divider, means we must strike a balance. The ethical dilemma at the heart of AI adoption is how to pursue innovation without sidelining the most vulnerable. Solving this requires conscious action from international bodies, policymakers, and corporations:

Global Collaboration

International bodies like the UN should treat AI inequality with the same urgency as climate change. That means funding AI-for-good projects, creating shared open-source models, and ensuring no country is left in the digital dust.

Government Policy

Internet access as a public good. Nationwide re-skilling at scale. Social safety nets for displaced workers. Antitrust measures to prevent AI monopolies. These aren’t nice-to-haves, they’re the foundation of an equitable AI future.

Corporate Responsibility

AI firms must design for fairness, transparency, and inclusion. That means building with diverse datasets, running bias audits, and engaging communities directly in the design process. The most impactful AI solutions will come from co-creation with the people they aim to serve. Remember human-centered design? It’s not just recommended, it’s the right thing to do here.

Final Thoughts: The Ethical Test of Our Time

AI’s global spread is more than a technological shift. It’s a values test. Will it be the great equaliser, extending opportunity and prosperity to those who need it most? Or will it act as a turbocharger of inequality, widening the chasm between the haves and have-nots?

The answer depends entirely on the choices we make now.

The promise is clear: with creativity and compassion, AI can lift communities, be it a farmer receiving real-time crop advice that saves a season’s harvest, or a student in a slum accessing the world’s best tutors through a mobile phone.

The risk is equally stark: without deliberate action, the default trajectory leaves the marginalised further behind. A factory worker replaced by automation, a developing nation excluded from the AI-driven economy.

Ultimately, the rich-poor AI dilemma comes down to one principle: inclusion by design, human-centered design. Technology alone doesn’t guarantee progress. It’s only equitable when built on human-centred design that actively works to include, not exclude.

AI isn’t destiny. It’s a mirror. What it reflects back will be less about algorithms, and more about the values we code into them.

🫶🏻 Thanks for reading till the end.

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The Future of Growth Marketing: How AI Is Rewriting Roles, Skills & Strategy

As AI reshapes industries, growth marketing is evolving at lightning speed. Discover how roles, skills, and tech stacks are transforming — and what it takes to thrive in this AI-first future.

Week 2 of my BCG DTCM course, and the hot topic? Disruptive Tech. One hot question that sparked the room like pineapples on a pizza:

“How will GenAI reshape our industry roles?”

Let’s be real. Growth marketing isn’t what it used to be. The era of pulling manual levers, tweaking campaigns like a fidgety sound engineer, is fading fast. What’s replacing it? A high-stakes symphony of orchestration, automation, and strategic intuition. AI isn’t just another tool, it’s the accelerant.

And in this new world, you either adapt… or dissolve.

This isn’t a blog post about the future. It’s about how the future is already in your inbox, your Slack channels, and your MarTech stack, quietly rewriting job descriptions, skillsets, and the definition of “growth.”

Let’s unpack what’s coming next and why the smartest growth marketers won’t be the ones who resist AI, but the ones who run toward it with curiosity, creativity, and a killer prompt library.

1. Where Are We on the AI Curve?

Before we chase the future, let’s locate ourselves on the map.

Enter the Technology Adoption Curve:

Innovators → Already knee-deep in GenAI.
Early Adopters → Moving fast, setting the bar.
Early Majority → Testing the waters, cautiously scaling.
Late Majority & Laggards → Watching, doubting, delaying.

🧠 Reality check:

Over 50% of companies are experimenting with AI. But only a handful have embedded it deep into their growth engines. Most sit awkwardly between Early Adopters and Early Majority — flirting with potential, but afraid of commitment.

💡 Key takeaway:

This is the window of advantage. Move now, or risk being outpaced by competitors with AI copilots.

2. The AI Framework: People, Processes, Platforms

A. People: From Marketer to AI Orchestrator

The role of the growth marketer is being redefined.

Forget “account manager.” The new power player? The AI Orchestrator.

🎻 Think conductor of a high-speed, data-fueled symphony, instead of a one-man-band stuck in spreadsheets.

🆕 Emerging Roles:

Growth AI Strategist
Growth AI Agent Trainer
AI Personalisation Architect

🛠️ Evolved Skillset:

Table stakes: data literacy, prompt engineering, AI ethics
Still undefeated: storytelling, brand strategy, empathy

💥 Big idea:

It’s not man vs machine. It’s man with machine — and the best humans will know how to speak “AI” fluently.

B. Platforms: Rise of the Intelligent Stack

Tech stacks are getting smarter. And they’re choosing sides.

🤖 AI Agents that Dominate:

Automated media planning. GenAI content engines. Smart CRMs that think ahead.

🛠️ No-Code/Low-Code Uprising:

Want to launch a predictive workflow without IT? You can. (And if you can’t yet, your competitors will.)

🔗 Integration Is Survival:

Disconnected stacks are dead weight. The winners?

Platforms that speak fluently across data, content, and decision layers.

C. Processes: From Muscle Memory to Machine Learning

We’re not just automating tasks. We’re upgrading how growth happens.

⚙️ Hyper-Automation Meets Agentic Workflows:

Campaign setup, A/B testing, reporting? Handled by tireless agents.

⚡ Real-Time Optimisation:

Budget shifts. Creative swaps. Targeting pivots. All live. All the time.

🔁 Continuous Learning Loops:

Every touchpoint becomes a lesson. Every lesson refines the next move.

Welcome to compounding intelligence.

💡 Big idea:

The new growth playbook will write itself (literally).

3. Impact: Efficiency + Effectiveness Redefined

📉 Efficiency Gains:

What used to take a week now takes a day.

Manual labour? Out. Smart automation? In.

📈 Effectiveness Boost:

Hyper-personalised ads. Smarter segmentation. Sharper predictions.

ROI isn’t just better, it’s rebuilt for the AI age.

❤️ The Human Edge:

While AI handles the “how,” humans own the “why.”

Strategy. Taste. Judgment. That’s your moat and no algorithm is crossing it any time soon.

Final Thoughts: Adapt or Fade

Let’s cut through the noise: the future of growth marketing isn’t coming, it’s already rewriting your job description.

The next wave of growth roles won’t be won by those who can list the most tools on their resume. It’ll be led by those who know how to think with them: strategically, creatively, and ethically.

Yes, AI is the new intern. But it’s also your strategist. Your analyst. Your ops assistant that doesn’t sleep.

Still, even the smartest AI needs a boss. One with taste, vision, and the emotional IQ to understand “why,” not just “what.”

This isn’t man vs. machine. It’s a collaboration.

But make no mistake: those who resist evolution will be replaced by those who embrace it.

🧠 Key takeaway:

The debate isn’t over. It’s just beginning.

Are you ready to evolve or be out-evolved?

🫶🏻 Thanks for reading till the end!

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The Growth Stack for Your Brain: AI Tools That Boost Your Output

Discover how growth marketers and PMs can build an AI-enhanced growth stack for their brain. Learn how to offload research, writing, and analysis, delegate smartly to AI tools, and avoid the over-tooling trap to boost productivity and think smarter, not harder.

Imagine if ChatGPT, Notion AI, and Perplexity were your interns. Now imagine they worked 24/7.

That thought hit me hard during a recent conversation about the ideal marketing technology stack. We were deep in the weeds of tools, integrations, and automation when it struck me: why not apply the same thinking to how we run our brains?

Because here’s the uncomfortable truth: the modern growth product manager isn’t just competing against their peers. They’re competing against peers who’ve built smarter workflows. People who’ve turned AI from a shiny new toy into a relentless cognitive force multiplier.

In this new game, AI tools aren’t “nice to have.” They’re your new growth stack for your brain.

But this post isn’t a listicle of shiny tools. It’s a framework. A mindset. A way to architect workflows that scale your cognitive capacity and free you to focus on the work only humans can do: empathy, insight, strategy.

Ready to upgrade your mental OS? Let’s begin.

Why You Need a Growth Stack for Your Brain

Cognitive bandwidth is your scarcest resource. It always has been. The difference now? You can finally scale it.

The AI revolution isn’t about replacing humans, it’s about augmenting them. Think Iron Man, not Skynet.

For PMs and growth marketers, this is especially true:

You swim in a constant flow of information → you need rapid synthesis.
You face relentless pressure to create → you need faster execution.
You make strategic decisions daily → you need sharper insights.

The takeaway?

Great companies (and great individuals) compound productivity over time. Today, the same applies to your brain. The right stack doesn’t just make you faster, it makes you better.

Core Principle #1: Offload Research, Writing, and Analysis

Research

Perplexity AI is your always-on research analyst. Unlike search engines that spit out 10 blue links, it delivers distilled, conversational answers.

The key? Learn to frame smart prompts that go beyond Googling.

Example: Competitive intelligence → compress a full day of desk research into 15 minutes of AI-driven synthesis.

Writing

ChatGPT and Notion AI are your ghostwriters on call. Use them to:

Draft the first versions of blog posts
Summarise meeting notes
Craft investor updates
Generate marketing copy variants.

AI helps you get to a clear first version faster, freeing your brain for editorial magic — the human part that makes content resonate.

Analysis

Pair ChatGPT with Google Sheets or Notion AI to turn data into insight:

Summarise large datasets quickly.
Extract themes from audience feedback.
Conduct an exploratory analysis.

Example workflow: Feed in raw survey responses → Auto-summarise emerging themes → conduct human review to layer in nuance and empathy.

Core Principle #2: Smart Delegation to AI Tools

Think Like a Manager of AI, Not a User of Tools

AI is your intern, not your strategist. You define the “why” while it handles the “how.” If you abdicate thinking, you’ll get generic output.

Create Repeatable AI Workflows

Build systems, not hacks:

Example: Weekly competitor watchlist → Automated Perplexity briefs.
Example: Monthly content calendar → Notion AI-generated ideas, seeded from your audience data and product roadmap.

Where Human Judgment is Still King

Some domains still belong to humans:

Brand voice → can’t be automated.
Strategic trade-offs → require wisdom.
Empathy-driven communication → only a human understands the human condition.

The tool doesn’t do the work. The tool amplifies the work you decide is worth doing.

Read more here about how AI is revolutionising Performance Marketing.

Core Principle #3: Avoiding the ‘Over-Tooling’ Trap

The Shiny Object Syndrome

Beware the lure of more tools = better outcomes.

Warning signs:

Constantly switching tools, chasing marginal gains.
Over-automating to the point where craftsmanship suffers.

Choose a Minimal Stack

Start lean and build depth:

Suggested trio: ChatGPT + Perplexity + Notion AI.
Build muscle memory with these first. Mastery > Novelty.

Balance Automation with Human Creativity

Remember: Magic happens at the intersection of AI efficiency and human curiosity.

AI should give you back time and space. What you do with it is where the real value lies.

Tools don’t create growth. Focus does.

Final Thoughts

So, let’s recap:

Offload the mechanical — free up your brain by automating research, writing, and analysis.
Delegate smartly — treat AI as your tireless intern, not your strategic brain.
Beware the tooling trap — simplicity scales, complexity kills.

Now, here’s the truth: The growth marketer and PM of the future won’t win because they know the most tools. They’ll win because they know how to think better with them.

As Malcolm Gladwell said, “Practice isn’t the thing you do once you’re good. It’s the thing you do that makes you good.”

The same applies to your AI-enhanced brain. The more you practice working with AI, the more powerful your thinking becomes.

So here’s your challenge:

Build your personal growth stack this week.

Start simple. Learn deeply. And when you discover what works, share it. Let’s trade tips and level up together.

🫶🏻 Thanks for reading till the end.

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Smarter, Not Harder: How AI Is Revolutionizing Performance Marketing

Discover how AI is transforming performance marketing — from Google’s AI Max to synthetic personas outperforming media teams. The future isn’t just automation. It’s smarter strategy, human meaning, and a redefined marketer’s role.

Two nights ago, I found myself in a room filled with LLMs, wine (and water), and wonderfully opinionated minds — a roundtable hosted by Future Forward AI, where the conversation spun around deceptively simple questions such as: is AI here to augment us, or to replace us quietly?

We discussed synthetic data. Accountability when things go south. And most provocatively, the new power dynamic at play: as machines become the decision-makers, where does that leave us, and for me, this refers to the growth hackers and the human strategists? Are we evolving into directors of the play… or just the extras no one remembers in the final scene?

This post is my reflection on that night — a deep dive into how AI is no longer knocking on growth marketing’s door; it’s already moved in, rearranged the furniture, and started running the show. From Google’s AI Max to agents outperforming human media teams, the signals are loud and clear: the game has changed.

So pour yourself a strong coffee (or a bold Syrah), and let’s uncork the future of marketing. Spoiler alert: it’s smarter. Not harder.

1. AI Is (Already) Redefining Targeting and Optimisation

Let’s start with the elephant in the ad account.

AI hasn’t just joined the marketing team, it’s rewriting the SOPs. The clearest sign? The way we target and optimise campaigns today.

We’ve moved from AI as an assistant (“Hey, help me clean up this audience segment”) to AI as a replacement (“Hey, you don’t need to build the segment, I already did. And I launched it.”).

AI isn’t just a better spreadsheet. It’s a strategy engine.

It reads signals, interprets intent, allocates budgets, and even rotates creatives, often in real time, across thousands of permutations.

Tools like Google Ads’ Performance Max and Meta’s Advantage+ aren’t just “helpful”—they’re becoming mandatory for anyone serious about scale and efficiency. You feed them assets and objectives, they run with the rest.

The result?

💼 Leaner teams.

🚀 Faster tests.

💰 Smarter bets.

💡 “We used to A/B test. Now we A/B delegate.”

The algorithm doesn’t just suggest. It decides.

2. AI Max: Google Just Gave the Algorithm the Keys

If Performance Max is the autopilot, AI Max is the self-driving car.

And yes, Google is firmly in the driver’s seat.

According to Search Engine Land, Google’s latest launch— AI Max for Search, hands over full autonomy to the machine. No more partial control. It dictates bidding, creatives, audience combinations, placements, and timing. All of it.

It’s not just about doing more. It’s about doing without us.

Why does this matter? Because it marks a tipping point. The marketer’s job is no longer to steer the car, it’s to decide where we want to go and let the machine figure out the how.

Let’s unpack that:

Algorithmic Bidding: Gone are the days of manually tweaking CPCs. AI updates bids every millisecond based on thousands of signals you can’t even see.
Predictive Audiences: The AI now predicts intent before users know it themselves. It’s targeting based on probability, not just past clicks.

🧠 “In the past, we optimised based on history. Now, we optimise based on probability.”

Welcome to quantum marketing.

3. AI Agents Outperforming Human Teams: The Tipping Point?

Still not convinced? Let’s talk outcomes.

In a recent case from Adweek, PMG deployed AI agents, built on Mobian’s synthetic personas, for a health brand’s campaign on Fox News.

Now here’s the mic-drop moment:

🧠 Just 18% of the budget went to Fox…

🎯 …but it delivered 34% of total conversions

💸 …at 46% lower cost per conversion.

Why? Because AI agents don’t rely on human gut feelings.

They pick up sentiment, emotion, and micro-signals no spreadsheet can see. They place ads not based on where you think your audience is… but where they actually are.

These agents aren’t replacing interns.

They’re replacing entire departments.

And they’re doing it by:

Creative Automation: Testing hundreds of variants in minutes. No approvals, no bandwidth issues. Just cold, calculated iteration.
Personalisation at Scale: AI knows when you’re stressed, sleepy, or ready to buy. Humans still think in personas. AI thinks in probabilities.

🤖 “What happens when the intern, the strategist, and the designer all show up… inside a single AI agent?”

The question isn’t whether AI can run your campaigns.

It’s whether you’re still needed in the room when it does.

4. But… What’s the Role of the Human Growth Marketer Now?

Let’s be clear, this isn’t the obituary for growth marketing.

It’s the redefinition of it.

The best growth marketers today?

They’re not writing copy or pulling audience lists.

They’re orchestrating strategy, interpreting insight, and setting the ethical and emotional compass of the brand.

Your job isn’t to out-optimise the machine.

It’s to ask better questions, shape better stories, and steer the AI toward impact.

Because let’s be honest, if 80% of your job is building dashboards, you’re officially in AI’s crosshairs.

🎹 “AI is becoming the pianist. You? You better be the composer.”

Final Thoughts: The Future of Performance Is Less About Performance

Here’s the paradox: the more AI nails performance (clicks, conversions, cost-efficiency) the less we need to chase it.

Machines are winning the execution game. But they can’t (yet) tell us why we matter. They don’t understand emotion, context, or culture. That’s still our job.

Your role isn’t to out-optimise the machine.

It’s to give it purpose. Direction. Meaning.

In a world of infinite automation, meaning is the new performance.

Key Takeaway:

The future of growth marketing is smarter, not harder.

Let AI handle the how. You focus on the why.

🫶🏻 Thanks for reading till the end.

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The AI Wars Just Got Personal: Google’s AI Agents Are Now Running Your Ads

Google just changed the rules of digital marketing at I/O 2025 with the launch of AI agents in Google Ads. Discover what this means for growth marketers, how to adapt, and why working with AI—not against it—is your next competitive edge.

So this just happened earlier this week… The AI Wars Just Got Personal and They’re Inside Our Ads Account

We are now living in the AI Wars, and Google just sent in the ‘Terminators’.

At I/O 2025, the tech giant didn’t just unveil new features. It unleashed a battalion of AI agents — smart, tireless, and fully integrated into Google Ads. For growth marketers, this isn’t science fiction.

Forget faceless robots waging war in distant dystopias. These are inside your ad platform, rewriting headlines, adjusting bids, and optimising performance before you’ve had your morning coffee. If ChatGPT were the polite intern, this? This is Skynet learning to run media buying.

And here’s the twist: it’s not here to kill your job but to challenge it.

The bigger AI picture is becoming clearer: OpenAI leads in user adoption, Microsoft in enterprise productivity, but Google is coming for the growth stack. With unmatched access to user intent (hello, Search) and now Gemini-powered agents baked into every corner of its ecosystem, Google is rewriting what it means to do marketing in the AI era.

This isn’t about automation anymore. It’s about augmentation, and the marketers who know how to ride the wave instead of running from it will be the ones standing when the smoke clears.

If you thought performance marketing was already moving fast, buckle up. The new era isn’t just faster — it’s smarter, always on, and increasingly… not human.

Google I/O 2025: What Just Hit Us?

Google didn’t just update its product roadmap. It reprogrammed the marketing playbook.

At I/O 2025, it launched a suite of AI innovations that feel less like feature upgrades and more like an existential retooling. The most headline-worthy? AI agents are now fully embedded inside Google Ads. They don’t just help marketers. They do what we used to do — only faster, cheaper, and without needing coffee or a quarterly bonus.

But before we jump to “machines-are-taking-over” paranoia, let’s decode the actual announcements and what they mean for us on the front lines of growth.

🧠 AI Mode in Search: From Keywords to Conversations

Google’s new AI Mode turns traditional search into a full-on dialogue engine. You no longer get a list of links. You get synthesised answers, action steps, and the option to “keep going” with contextual follow-ups.

For growth marketers, this is both a dream and a nightmare. A dream because the customer journey becomes frictionless. A nightmare because we now need to optimise for conversations, not just clicks. Your SEO strategy just got an AI-shaped curveball.

🌊 Project Mariner: Your Agent Will Google That For You

Project Mariner is Google’s multitasking AI assistant. It doesn’t just respond — it acts. Think of it as the intern who not only researches the best CRM tools but also signs you up for trials, syncs your calendar, and sends a Slack update to your boss.

Implication? Expect a rise in fully automated conversion flows — all handled by AI. From a growth perspective, this means our new funnel touchpoints may no longer be human at all.

🧬 Gemini 2.5 Pro & Deep Think: Strategy as a Service

The brains behind the operation are Gemini 2.5 Pro, now with Deep Think mode. This isn’t your average autocomplete. It simulates layered reasoning, evaluating options before delivering an answer, like an analyst who’s actually good at their job.

This upgrade unlocks new possibilities in campaign planning, budget modelling, and even creative strategy. You’re not just delegating execution to AI — you’re increasingly delegating thinking.

AI Agents in Google Ads: Meet Your New Teammate (or Replacement?)

Google’s bet is clear: AI isn’t just a tool — it’s the new teammate. And these AI agents? They’re here to handle the grind so you can focus on the strategy.

⚙️ Functionality

These agents chew through your campaign data, generate creatives on the fly, optimise bids in real time, and even draft your performance wrap-up reports. They’re not perfect, but they’re relentless.

📈 Smart Bidding, Upgraded

AI-powered Smart Bidding Exploration takes historical data, cross-references with live signals, and calibrates for ROAS like a hedge fund algorithm. It’s not just about cost-per-click anymore; it’s about predictive profitability.

🎨 Creative Superpowers

Pair this with tools like Veo and Imagen, and you’ve got a creative engine that drafts high-quality ad visuals and videos at scale. We’re entering a world where every growth marketer is also a creative director, without needing to learn Photoshop.

What This Means for Growth Marketers?

Now let’s talk reality.

This isn’t just another shift in platform mechanics. It’s a redefinition of what “marketer” even means. AI won’t replace your job, but it will replace parts of it.

So the question isn’t “Will AI take my job?” It’s: “Will I know how to work with AI, or will I be replaced by someone who does?”

⏱️ Efficiency Gains: The End of Busywork

You’ll spend less time toggling through dashboards and more time making actual decisions. That’s a win. Campaign builds, creative iterations, and performance reviews are all streamlined.

🧭 Strategic Shifts: From Operator to Orchestrator

You’re not setting the dials anymore. You’re telling the system what outcomes matter and letting it figure out the rest. The value now lies in judgment, creativity, and context, not in button-clicking expertise.

🧠 Skillset Evolution: The 2025 Growth Stack

To stay ahead, you’ll need:

Comfort with prompting and AI workflows
Fluency in interpreting AI-generated insights
The ability to spot strategic angles machines still miss

This is your call to upskill — not just with courses, but with curiosity. Learn to speak AI as fluently as you speak ROAS.

Read more about how AI is impacting Performance Marketing here.

⚠️ Challenges Ahead: Not All Smooth Scaling

Control & Oversight: What happens when the AI makes decisions that don’t align with your brand voice or creative instinct?
Transparency: Can you explain to your client (or your boss) why the AI paused half the ad groups at 2 AM?
Adaptation Fatigue: Yes, it’s exhausting. But the 1% daily improvement mindset? That’s your edge. Don’t chase perfection. Compound progress.

Read more about the 1% compounding effect of improving your life here.

Final Thoughts: Embracing the AI-Driven Future

In 2023, we learned to prompt. In 2024, we started experimenting. In 2025? We partner with AI, or risk being left behind by those who do.

Google’s latest announcements don’t kill the role of the growth marketer. They kill the old definition of what a growth marketer is. What rises in its place is someone more strategic, more curious, and more adaptable.

So, my fellow comrades, the war is on. But you’re not being replaced by a robot.

You’re being upgraded.

🫶🏻 Thanks for reading till the end.

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2023 Digital Marketing Predictions

At this point, doing a 2023 prediction now seems to be cheating. I admit that predictions are hard and it probably took me longer than I should to assemble my views. While better late than never, hopefully this will spark conversation and hold us accountable for our predictions.

AI-Powered Digital Marketing

Let’s start with an easy and obvious one – something I have already wrote about previously. Whether we like it or not, the rise of AI in Digital Marketing is upon us.

2023 is probably the first year we see the start of real competition to Google’s Search dominance in the form of Microsoft’s new AI-powered Bing. However, this hype about AI has already transcended Search marketing, and many Ad Tech businesses are eager to incorporate AI into their products.

With AI providing efficiency, what this means for Digital Marketers is the need to go beyond building deep technical expertise and instead focus on soft skills like problem solving, strategic thinking and creativity.

Focus on Enhancing Customer Lifetime Value

From a macro economic standpoint, 2023 is set to continue the tailwinds of a turbulent 2022. Rising interest rates, inflation and a potential recession.

With such a gray backdrop, more companies will probably prefer to be conservative with their digital marketing budgets. As such, to obtain growth in revenue, companies will need to extract higher value per user.

Companies should therefore focus on product and monetisation to enhance their customers’ LTV. Improving LTV will also reduce the opportunity cost caused by the rising interest rates.

Apple to Extend its Digital Advertising Dominance

Since Apple released iOS 14.5, the importance of Apple Search Ads to Digital Marketers has grown drastically. This has clearly revealed Apple’s ambition in the digital advertising space.

Apple’s strengths lies predominantly in its ecosystem. With full visibility of its audiences within the iOS ecosystem, Apple is in the best position to provide personalised ads and measure its effectiveness.

All Apple needs now, is to build its own ad exchange and demand-side platform.

Privacy Forces Transition to Probablistic Tracking

Towards the end of 2023, Google is expected to finally release its Privacy Sandbox initiative where it will reduce cross-site and cross-app tracking. This is almost equivalent to Apple’s iOS 14.5.

So, Digital Marketers should prepare for a world without deterministic tracking such as device IDs or cookies. The broad solution to this is probabilistic tracking and it is likely that advertising platforms will resort to using this.

Tiktok to Finally Overtake Meta and Google

Let’s face it. Attention spans are dropping globally. (If you made it to this point, kudos to you!) We have been saying it for years that video as a medium is the next big thing. Specifically in 2023, short-form videos will takeover the world. To combat Tiktok, Meta and Google have both released their own versions in the form of Reels and Shorts respectively.

It is probably still a stretch that Tiktok may actually overtake the two behemoths in 2023. But with as the fastest-growing platform dominated by youths, it is clear that the future, for now, lies in Tiktok’s hands.

In all, 2023 will definitely be another interesting year for digital marketers.

What other futures do you see yourself in 2023?