Today, I’m back with a reflection on where we are today.

This is the age old question. And usually for growth stage businesses, t…

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Inspired by New York Mag’s recent 247 things you should know as a New Yorker, we thought we’d compile our own version for you.

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Meta is shipping fast at the moment. When I initially wrote this, the latest ability to push spend to specific ads hadn’t been shipped. As I rewrite this, yet another new feature is launching. This is some of the most useful and fast-paced product development in Ads Manager we’ve s…

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With our first full week of Jan behind us, we’ve examined multiple categories and trading is on average slower than expected. As ever in times like this, I speak to friends who work in marketing and are founders.

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41 newsletters (42 including this one). Roughly 40,000 words. One year of thinking out loud about growth marketing, Meta ads, and building Ballpoint.

At the bottom of this newsletter, you’ll see a roundup of my top posts of the year. But first a reflection.

I’ve been blogging on some subject or other for over two decades now. No matter what it is I’m writ…

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Here’s my reflection on where we are as we go into 2026.

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1. Alcohol and the era of moderation

The IWSR recently published a report on drinking that did the rounds. There were two charts that showed the story.

First, is the absolute chart that reveals that Brits are now on a par with Americans for amount of alcohol drunk per capita each week.

There is a clear decline within the UK down to just over 10 drinks per week on average.

Gen Z’s role is shifting

The common narrative for a long time was it was Gen Z leading this charge, but data from summer showed that trend is bucking.

In fact, as that article suggests, a lot of Gen Z’s prior teetotalism can be accounted for being underage, unemployed or in less stable working environments generally. The generation is older, working and more affluent than they were in previous years.

And so overall declines in drinking in the UK must be broader.

Let’s look at that IWSR data again, but indexed rebased to 1990.

The shape of this chart got me digging into a few other thoughts of what correlates at this time.

A few key thoughts here:

• There’s a clear financial crash change around 2007-2010 that correlated with the downward trend

• Drinking rose throughout the 90s and peaked in early 2010s (just as I and other millennials starting drinking)

I was interested in how this correlated to public sentiment towards politics – whether the New Labour optimism was fuelling it.

What this means for brands

There’s a decline in drinking for sure, but it’s not as clear cut generationally as once thought. For anyone selling in the low or no alcohol space, this won’t be a surprise.

The bigger questions might be why this is happening. Understanding the motivations between reduced alcohol will help shape why and how to sell to someone.

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2. GLP-1 users are the new happy, premium consumers

GLP-1s are tricky beasts.

When I think of GLP-1s, my default is to think more of toxic culture of skinniness than it is to think of overweight people creating better relationships with their bodies.

I know statistically that isn’t correct. In the UK, the distribution of of weight leans far more to the overweight and obese end.

And when we look at global trends the picture is clear too:

Obesity is on the rise, and most sharply in the faster-growing middle income economies.

So this set of stats is interesting from the New Consumer report.

Life satisfaction is 14% higher for GLP-1 users than the average. And in fact is one of the best predictors for life satisfaction – second only to those who earn $150-200k/year.

Most interestingly for brands is what that increased life satisfaction correlates to in spending power.

Unlike the general population, where there is a mixture of trading up and down depending on category, GLP-1 users are almost trading up in every category from the Coefficient Capital survey.

Perhaps the surprising ones are in restaurant meals (17% up), and snack foods (24% up). But as their report also states a lot of this interest will come from new brands or products specifically catering for them.

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3. Drug use on the rise

While alcohol make be down, and low and no down with it, lots of drug use is on the rise.

18.1% of British 16-24 year olds have taken an illegal drug in the last year, which when you consider the 39% who never drink, might offer part of the picture.

In the US, while daily alcohol drinkers are flat or showing slow growth, daily cannabis users overtook drinkers a few years ago.

Meanwhile, lifetime use of cocaine has doubled since 2001 at a time when regular drinking has declined significantly. The overall numbers are still far apart, but the relative trend is clear.

It is too simple to look at alcohol moderation and say that society is moderating. For some, it is definitely about blanket moderation, but for others one drug is being swapped for another. And in many cases, some of those swaps will be worse rather than better.

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4. Longevity is on the rise

2025 started with the Don’t Die doc landing on Netflix. At the time, everyone laughed.

Today, the laughter seems to have quieted down.

Lots of biohacking is expected to rise.

Oura Ring sales have close to tripled in five years.

£200m is being spent on anti-ageing in the UK.

I had an IV in early December, and part of that was a NAD shot. NAD is still expensive to get as an injection or home shot. Most packages you’re looking at £300+ per month to properly get the benefits.

The number of people who will spend £3,600 per year on this is low. But this is the tip of the iceberg for the market.

5. Comms & storytelling is more important than ever

My old boss, colleague, board member Peter Sigrist used to consistently extol the value of storytelling. Whether it was in corporate comms, education, politics, or now quantum computing, I’ve never heard someone so stalwartly defend the value of being able to communicate a narrative.

Turns out the world is waking up to Peter’s worldview.

This year, we saw all the big AI companies invest heavily in storytelling, comms-focused content positions. It caused a few eyerolls given what these companies are doing for broader content around the world.

But as this WSJ article reinforced, it’s never been as important to find storytellers in the world. Source.

• The number of roles including the word storyteller have doubled year over year.

• This isn’t just marketing, companies want specific storytelling skillsets

• Continuing trend of owning your own content distribution

• Huge salaries to go with it

In advertising, this is important too, but while adverts try to capture attention in nano-seconds, this feels like the longer sell once you get someone into your world.

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6. Confidence in consumer investing is back

Sugar Capital, the venture arm from the POPSUGAR founders, posted a call to arms in early December with their post “The Golden Age of Consumer Investing.”

I read Brian Sugar’s post enthusiastically.

“A gummy vitamin company reaching $300 million in revenue on $20 million of primary capital. Contribution margins above 40 percent. Meaningful EBITDA before the Series B.”

“Product-market fit” is bandied around a lot in startup folk lore. I know it because I had my own startup fail without it. But so much discourse around PMF is focused on enterprise, b2b, and proper tech companies. You have comments referring to how sticky user engagement is or what your DAUMAU ratio needs to be. And how to solve it is focused on switching product categories or strategies with winners the likes of Twitch, Instagram, Notion, or in the UK more recently Fyxer.

But a lot of PMF discourse doesn’t talk to consumer non-tech problems.

At Ballpoint this year, we’ve worked with over 50 brands, and I’ve audited maybe another 150. We see up close and personal the companies that:

1. Don’t have PMF and is unachievable unless something massive happens

2. Do have signs of PMF, but haven’t worked out how to scale a growth engine yet

3. They have it, they’re scaling, but want to push harder because they’re in a growing category and need to be dominant

When Brian talks about contribution margins and ebitda, this is not an outcome of modern consumer PMF – it’s a part of it. PMF is about sustainable business models and huge accelerated growth opportunities. You need to a path to $200m and you need 30%+ CM.

Health is the focus

It’s unsurprising perhaps that this post has focused so much on health. Brian puts down this new wave of optimism to health specifically.

“Something shifted in American consumption over the past five years. People read labels. They actively avoid the processed food that built the twentieth century’s largest companies. Ozempic and its cousins rewired how America thinks about what it puts in its body.”

We share Sugar Capital’s optimism and focus.

7. There’s still scepticism in the M&A markets

Before you start pulling money from your index funds to invest in early stage consumer, there’s still some scepticism in the market.

The excellent Drew Fallon in his Substack Making Cents, posted this week the “2026 M&A Outlook.”

In it he highlighted just a few of the big issues we’re facing at the moment. Namely:

• Coca-Cola are trying to get rid of Costa for $2bn having bought it for over $5bn

• Waldencast are maybe selling Obagi

• Estee Lauder are likely to sell off some brands

• LVMH is trying to shift its 50% stake in Fenty

• Nestle wants to further investment in health and is reviewing elsewhere

And the list goes on.

It wasn’t all doom & gloom, as Drew pointed out interest rates are likely to continue dropping in the US and that will be good news for all. This will particularly be true for the portfolios with lots of DTC weighting which are now approaching the end of the 8-10 year fund cycles. Expect lots of pressured dealmaking for brands in this part of the cycle.

And the areas Drew has the highest confidence in:

“Protein and fiber [sic] companies (and hydration to a lesser extent) that are gobbling up market share right now are critical assets that must be owned”

This said, however, 2025 ends with broader M&A at an all-time high with $4tn in dealmaking done this year.

8. The two horsemen of the 8-figure world: LTV debt and Brand debt

I was reminded of Sean Frank (the Ride CEO)’s comment this month about Stanley:

Go back two years and Stanley were unavoidable. They were on every Meta ads inspo board out there. They were being case studied. And now they’re in a clearout section.

If you were YETI, who of course are broader in catalogue than Stanley were, you could have easily fallen for switching strategy. Fortunately their Google Trends data shows a slow but steady move up and to the right. They’ve remained stable and growing, while Stanley hit a hype curve they couldn’t follow back from.

We don’t know Stanley’s unit economics, but it’s a pattern we see often:

1. Hype doesn’t create a brand

2. Beware of LTV debt.

9. Beware of category cycles

This was a great chart shared by Ben recently about category/brand growth.

One key thing jumped out for me here about how to think through strategy.

Lots of businesses I know and meet aim for contribution break-even or contribution-profitability and their goal is to scale up to that point. In early days it’s a good strategy because it helps you build up to a level of net margin profitability by building enough revenue to cover your opex.

But once you’re there, you should think about category.

Now every founder is biased towards the strength of their own category. You are after all a founder and have long term belief in it.

But trends are cyclical. Just because GLP-1s and healthy snacks are big this year, it does not mean that’s a permanent state. We’ve seen in the space of a decade the explosion and death of artificial meats. The things that were rampant for millennials are unimportant for gen z and so on.

The move towards green looked like an inevitable change for the 2010s, but there’s backlash against it now. Governments, populism, consumers are shifting and moderating.

We are in a health cycle at the moment, and so lean in to your strengths. Lean into the growth.

But also make sure that you are not creating fragility. Running at £0 net profit is better than negative. But if you’re in the position to have customer growth for the benefit of cash flow growth – and you’re in a cycle that could change – then build in some optionality.

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10. The constant battle with affordability

The West seems to be battling away a recession every month. Only 42% of Brits believe they will ever be able to afford to buy a house. 56% of Brits say they’re impacted by the cost of living crisis this year.

Amongst young people, it’s the single biggest issue affecting the country. More than seven million people in the UK are going each month without essentials.

And amongst the highest earners, tax rates plus loss of child benefit mean that if you’re earning £125k per year, you’re actually worse off than earning £99k per year.

There is a higher number than ever who forgo basic necessities. There is a growing middle who who without support from Bank of Mum and Dad can’t afford housing. And the country’s best earners are disincentivised to earn more.

The ongoing joke about millennials is if they ditched flat whites, they’d be able to afford housing. Except for many, all that saving in the world won’t get them on the ladder. For them, buying premium makes sense.

There is of course lots to be optimistic about in the economy. But it’s also important that brands really think seriously about what type of company they are. Who they appeal to.

Are you really a mass market product? Or are you super premium? Does your growth and ambition support your customer?

And equally important are you actually talking to your customer in the right way? How you speak to middle England Facebook 50+ people is not how you speak to Real Housewives of Clapton London.

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Closing thoughts

The world feels more mixed than ever. Some macro signals are noisy and potentially worrying: ongoing affordability crisis, M&A scepticism, category cycles that could turn at any moment. On the flipsde, certain classes of consumer are spending more than ever in newfound categories, giving an opening to new types of brands.

Health, longevity, and alcohol moderation are certainly all singing in unison. But it’s not universal – THC products in the US continue to be prominent, and illict drug use is on the up in some categories as well. Not everyone is following the Bryan Johnston playbook quite yet.

Whatever type of consumer business you’re building, profitability remains king. Strong and early contribution margin is vital, but building net profit growth into your business is what is going to make M&A accessible.

The best founders and teams I’ve spoken to this year are all building optionality. They’re not content with cheap acquisition costs or break-even CM, they’re focusing on LTV debt and building cash into the business. Profitable enough to survive a downturn. Ambitious enough to lean into growth when the window opens. And perhaps most importantly, more realistic about who their actual customer is than ever.

If I was the founder of a growth business at the moment, I’d be using 2026 to think about ebitda profitability rather than fragile 100% growth maximisation.

We’re not in a universally good time, but for certain sectors it certainly feels like it.

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AI became a real possibility for ads creation this year.

At the centre of much of the AI backlash is the fear for …

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September was brutal, and by many degrees worse than last September.

I published mid September this chart on LinkedIn and it got a lot of conversation going.

Off the b…

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Since we’ve published this post, we’ve significantly updated our AI thinking, which you can read here.

AI is now the most frequent conversation topic of anyone in business I know now. One of our copywriters Mark said to me recently that “every conversation eventually turns to AI”. It’s become the modern Godwin’s Law.

There is a mixture of excitement and anxiety.

The AI influencer community is already in full swing accelerating that anxiety. If you believe every AI influencer then you might think there are entire companies now fully operated with just 25 AI agents and one person. You’re probably worried you’ll be left behind.

Anxiety in times like this is good. One of the best business books you’ll ever read is Only the Paranoid Survive by Andy Grove. The period we’re going through now is one of existential change, and if you bury your head in the sand, you probably will be left behind. Realising that this is an issue is important.

But at the same time, once you dig in to most of what the AI world is currently selling in today-terms, I’m often left wondering how many people actually use all of this day-to-day?

And what is there today that can be useful, recognising that ultimately every part of a system and workflow today will likely feel old in six months time.

I want to share very openly how we’re experimenting at the moment and our approach to it. I hope this is less a ‘here’s stuff you can borrow to be better at growth’ and more ‘here’s how we could experiment in our organisation' specifically.

Things to cover

1. How we ran our recent AI hackathon/weekender

2. Key lessons learnt

3. What we built

4. What comes next

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How we ran the AI Weekender

Most teams I know now are highly lean. Revenue per employee as a metric is back. And with AI companies now reaching tens and hundreds of millions with only a handful of employees, that will only continue.

But one of the issues with operational efficiency is that it doesn’t allow room for experimentation and play.

New systems and technology require experimentation and play. And there’s only so much snippets of time in evenings and weekends you can do to properly explore.

This was the backdrop to why Fiona, our head of ops and creative studio lead, and I went and did an our own Weekender. Except it wasn’t over the weekend, and we didn’t go clubbing. We spent two days of blocked out, deep work time, off site working only on AI.

Here’s how we did it

• Booked a workspace and hotel away from London to create different environment setting

• Blocked out calendars entirely, did handovers as if we were on holiday

• Came up with a long list of ideas ahead of the two days of what we wanted to build

For us this meant two days in Guildford where we worked solidly in deep work mode on AI ideas for two days.

What do we really mean by AI?

In this context important to point out the parameters.

1. The use of AI within automation frameworks to help us automate things we couldn’t have done previously

2. Exploration specifically of AI tools and how we could bring those into our workflows

How we worked throughout the day

We had a Notion board with our long list of ideas, and we then gave each an expected value.

We measured: (1) potential forecast contribution margin over a year the initiative could bring to the business and (2) probability we could finish it in two days

The CM forecasts looked at:

1. Can this reduce existing human time to the business?
   For example, can we replace 90 minutes of human time per week with 5-10 minutes of human time by automating a repetitive process? And therefore we can calculate 75 minutes of salary x 52 weeks of the year to give us a CM figure.
   

2. Can this accelerate our ability to do our jobs better and therefore increase client spend, which would then increase our revenue as well?
   Harder to forecast, but to be simplistic, let’s assume 1 ad in 20 we create allows us to push client spend by 15% per month, does this activity increase that ratio to be 1 in 18 and therefore offer a 10% increase in potential revenue to the business? Apply our gross margin to that revenue increase multiply it by number of clients it would impact, and hey bingo we’ve got a CM figure.
   

3. Does this activity reduce the likelihood of churn through better servicing of the client?
   Another hard to forecast one, but we have a set of principles we believe are important to client retention. Can we improve our ability to do that through an activity? And to do this we looked at our churn rate across the year, forecast a cost of churn in revenue terms, and again applied the CM calculation to it.
   

4. Does this improve our marketing of our agency?
   Very hard to quantify as measuring individual pieces of activity within the agency’s marketing is difficult. Yes we can look at substack reads/engagements, or LinkedIn likes, or follower increases, but ultimately, we don’t have a good answer to specifically how much that ties back yet.

And then we did a probability forecast of likelihood to complete within two days.

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Key lessons learnt from our AI experimentation

1. Computational thinking

First and foremost, this felt closest mentally to coding work that I’ve done in a long time.

This is process of approaching a problem in a way a computer scientist would do. It requires thinking through the ideas of like data structures, inputs and outputs, loops, and abstraction.

I’ve done CS50 in the past, and am fairly good at SQL, but I never really got into a proper language. I found it incredibly useful however, to understand things like defining variables, or iterating across loops.

For anyone who’s never done any coding or computer science stuff, in plain English this means:

• Breaking apart your day-to-day actions into the tiniest and most specific steps. For example, you might say:

  • press the button on the top-left of the coffee machine that has a has a circle with a dashed line through the top of it.

  • Wait for two minutes until the machine stops making any noises

  • Put your hand on the handle of the wooden block above the coffee machine, grab it, and move it to the right.

  • Pick up the bag that sits on the lowest shelf (position 0), on the far left of the shelf. Check that the bag says “coffee” on it.

  • and so on

• When presented with an either or action, using IF statements to set conditions and directions. For example:

  • IF the coffee machine has no coffee in it THEN add coffee to the back ELSE continue to next step

• Thinking about everything as data. I.e. every action or object or anything needs to be a data structure. And to use them properly, you’ll need to define them a lot. For example:

  • Every object in the cupboard is an object in a data array with different parameters

  • Every mug on the shelf is a different object

• When presented with a list of tasks you want to repeat for a list of things, ‘iterating’ with a ‘for loop’, i.e.:

  • For every object in the cupboard:

    • Check that it says coffee on it

I always find the first few easy to comprehend, but for the last one, it’s amazing how frequently you have to think like that when it comes so naturally as humans.

🌟 Key lessons: be prepared to think computationally and it would probably help to go and do lesson one of Harvard’s CS50.

2. What to automate

One of the first things we tested was seeing how we ChatGPT could automate analysis of different adverts.

It was one of the four hour deep pieces of work that worked based on a series of triggers or prompts. Ask a question about an ad in Slack? Great it gets an AI response reviewing the ad. Have an ad automatically hit a certain spend threshold, great get it to analyse.

It was technically beautiful.

Except the actual raw prompt at the end wasn’t something we ever do manually. We use AI a lot but we don’t use it that much in analysis and find humans far better analysts of visuals at the moment. So why did I think automating a route would be better.

🌟 Key lessons: only automate a process you have already tested

3. You do need the time

I context switch 9 or 10 times per day. Most work I do fits into 15, 30, or 60 minute chunks of time. If it doesn’t fit into that I have to make time for it.

With AI, it takes 60 minutes just to get your head back into a problem.

Inevitably, it could take another 60 minutes until you figure out how to solve it.

Then you need another hour to test it, let it break, and go and rebuild it.

And then you’re at a point that it’s done.

And so, you really do need to set aside big chunks of time. And given how many meetings and usual day-to-day work people have, I imagine that’s impossible to properly do without building that time in.

🌟 Key lessons: you can’t do AI properly in 60 minutes. It needs days.

4. It doesn’t naturally suit my mindset

I am very much a “done is better than perfect” person who is “vision, not detail.” I’ve hired exceptional people who are the opposite to that, but this level of work does require going very deep and stuff works or it doesn’t.

I still think AI sits with leadership to properly learn and implement, at least for us, but I’d murder a technical co-founder right now.

🌟 Key lessons: it suits perfectionist, detailed-orientated people

5. I now know n8n & how APIs work better

I always knew sort of how APIs worked before but now I get them a lot better. I’d still like to do a bit of a crash course on them rather than learn by doing. And want to explore Postman a bit so I get really comfortable – maybe even via Terminal. But overall my knowledge is 0 to 1.

🌟 Key lessons: n8n & APIs are great

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What we built

“This is all well and good Josh, but what did you build?” I hear you cry.

Ok. Here’s what we achieved.

Auto-generate simple statics using created backgrounds on nano-banana

GenAI comes down to great prompting. Great prompting is a skill that a handful of people have on the team but not every one else.

Workflow

1. Notion card where you drop a product link and a description of a scene

2. n8n takes that and sends it to ChatGPT

3. ChatGPT takes your input prompt and generates 10 variants of that prompt.

4. Each of those prompt get sent to nanobanana

5. Results come back to a thread on Slack and go to a Google Drive

Analyse recent creative winners

This was the ‘fail’ because we don’t use AI to do our visual analysis usually, but we got it working with a few inputs.

Workflow

1. Either (A) field updated on Notion, or (B) specific adname requested in an internal-client channel

2. Data is joined with other data from Notion related client insights

3. Claude prompt combines visual + insights and asks questions to analyse it

4. Result gets returned to Slack

Call actions shared to internal client Slacks

This never seems to work 100% but it does cover 90%.

Workflow

1. New Fathom call transcript

2. Transcript gets uploaded to Claude with a prompt about being marketer/exec assistant

3. Asks it to pull out all of the actions discussed on either side

4. Share those actions to client slack afterwards

High/Low Spend Alerts

We did get the non-AI version of this working. Still to build the next layer.

Workflow

1. Check Meta every hour across all clients to pull spend + conversions, then calculate CPA

2. Share the CPA update at a few key points to internal client Slacks

3. Check against a “danger” and “great” CPA range and if it’s good then either WhatsApp account owner / DM the account owner.

The bit here that’s not AI-ed is step 3, I’d love this to be relative to overall performance “recently” rather than set CPAs like this. If you’ve got ideas on how to build, let me know.

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What comes next

We’ve got 20 unfinished AI initiatives and dreamt up plenty more. I’ve also been tinkering away more at weekends and evening. It’s addictive.

We will also likely bring on someone to support with AI as a focus at least on a freelance basis while we build in additional workflows. But ultimately it’s still something I’m investing a lot of time in.

How we implement this amongst the team, tbc. Lunch & Learns are definitely one thing, but ultimately it’ll probably be something we do at the next offsite and dedicate a four hour chunk to so people can understand the true power of it.

I still haven’t done any vibe coding, but that is coming next.

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🔗 When you’re ready, here’s how Ballpoint can help you

→ Profitably grow paid social spend from £30k/m → £300k/m
→ Create full funnel, jobs to be done-focused creative: Meta, TikTok, YouTube
→ Improve your conversion rate with landing pages and fully managed CRO
→ Maximise LTV through strategic retention and CRM - not just sending out your emails

Email me – or visit Ballpoint to find out more.

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