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

This is the age old question. And usually for growth stage businesses, the answer lies somewhere in either product or marketing.

But perhaps the biggest factor is the one that we can’t control: the macro environment we all exist in.

We get glimpses of the macro as an agency when we analyse internal trends across £1.5-2m of ad spend each month. But sampling data like this is only part of a picture and is often more swayed by a particular strategy being deployed at any given time.

A lot has changed since the start of the year

This year has seen some pretty momentous change.

AI is now ubiquitous and we’re starting to see the real life impact of it, rather than the hypothetical (and this is before we get into future models).

But perhaps more immediately and tangibly impactful is the war in the Middle East.

Today’s post analyses a handful of sources including:

• Think tank releases

• Articles I’ve been reading the last few months from the Economist, FT etc

• Google Search Trends Reports

• Reddit

For most brands we work with, Q2 is a strong quarter that precedes the year’s weakest quarter, Q3. If I could predict the future, I’d be a rich man, but there’s still quite a few things I’ve seen so far that seem worth talking about.

Because I imagine this stuff will be having an impact for all of us in the coming months.

Josh

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29% of UK workers admit they’ve sabotaged AI tools at work

29% of UK workers admit they’ve sabotaged AI tools at work, growing to 44% for Gen Z.

The TUC finds 51% of the UK public concerned1, rising to 62% among 25 to 34 year olds.

There are hundreds of threads discussing AI anxiety in the last 30 days alone.

You won’t find this in Google Trends: searches related to “AI replacing jobs” have faded since April 2025. But ChatGPT usage in the UK tripled last year2.

Mortgage renewal, tax drag, and AI fear are hitting millennials at once

1.8 million mortgages expire this year into higher rates.

Frozen tax bands cost a £55k earner over £1,000 a year. And 52% of workers believe AI threatens their job.

On r/UKJobs, a 43-year-old on £50k described weighing a £27k offer.

On r/HousingUK, a first-time buyer watched their monthly payment jump £450 mid-conveyancing. No single dataset proves all three pressures act together. But the Reddit threads tell the same story from different angles: 30-to-45 year olds are absorbing rising costs, tax drag, and career uncertainty at the same time.

That’s the age group many premium DTC brands say drives their core revenue.

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Last time oil crossed $100, consumer mood fell 21 points in a month

In March 2022, Brent crude crossed $100 after Russia invaded Ukraine. Consumer mood (measured by the GfK survey) dropped from -17 to -38 in April.

By September it hit -49, the lowest in the survey’s 50-year history. In 2026, Brent spiked to between $109 and $1133 in early April on Strait of Hormuz tensions, and consumer mood is already at -21.

The pattern is the same: oil shock, energy prices rise, mood collapses. What’s different is the starting point, and what’s layered on top.

In 2022 the extremes won and the middle lost. It’s starting again.

After Brent crossed $100 in 2022, Aldi gained 1.4 percentage points of grocery share in 12 months.

Combined with Lidl, discounters grew 25% year on year against a market growing 7.6%.

Premium brands held.

In 2026, the same pattern is forming: Lidl is up 9.6%, Waitrose up 5.8%, Asda down 0.9%4.

If the 2022 pattern repeats, the middle loses the most share over the coming quarters. But there’s a difference this time: people are also dealing with AI job anxiety and a wall of mortgage renewals that didn’t exist in 2022.

People feel fine personally but are terrified about the economy

The UK’s main consumer-mood survey, run by GfK, asks two different questions.

How do you feel about your own finances?

And how do you feel about the economy?

The answers are diverging sharply.

The personal finances score sits at -7. Not great, but stable.

The economic outlook score collapsed to -37 in March, down 6 points in a single month and 8 points worse than March 2025.

That 30-point gap is the story. People aren’t struggling. They’re bracing. And bracing shoppers don’t stop spending entirely, they just get harder to convert.

People are saving more and spending less on big purchases

The GfK Savings Index rose 6 points in March to 27, the highest reading since January’s peak of 28. Context matters: it was 28 in January, fell sharply to 21 in February, then rebounded. So this is a recovery, not a breakout.

But GfK’s own consumer insights director put it plainly:

When people start saving instead of spending, brands need to earn the conversion harder.--

Health and beauty spending is up 6-8% while everything else flatlines

Note that this is February data and doesn’t capture most recent changes.

Barclaycard’s February data shows health and beauty up 6.4%, following 8.0% in January5.

Digital subscriptions grew 12.2%.

Entertainment grew 9.9%.

On the other side: household goods fell 2.9%, electronics fell 5.8%, airlines dropped 6.9%.

Overall spending grew just 1.0%, well below inflation of 3.2%.

People are choosing where to spend, and health is winning. Worth noting: this is February data, before the Strait of Hormuz oil shock.

Health and beauty was the most resilient category going into that shock, which is exactly the category you want to be in coming out of one. That resilience held through the oil spike. UK searches for strength training and gym memberships kept rising through March and early April, even as Brent crossed $100. Wellness isn’t a line item people cut first when the news gets worse.

“Strength training women” searches are up 261% in two years, protein powder peaked

Google Trends data for “strength training women” shows a 62% increase year on year and a 261% increase over two years. “Protein powder women” is up 80% over that same two-year period. Gym membership searches are up 88% year on year. This isn’t a January resolution spike. The trend has been compounding for two years and it’s still accelerating. The UK women’s health supplements market is worth an estimated £1.18bn, growing at 5.7% a year.

Vinted UK is up 80% and near all-time highs

“Vinted UK” sits at 93 out of 100 on Google Trends.

That’s up 80% year on year and 87% versus two years ago. It’s near the ceiling of search interest.

Meanwhile, ASOS reported sales down 9% globally and 5% in the UK in the first half of their financial year.

The secondhand market isn’t a niche. Every fashion DTC brand’s customer is now comparing prices against what they could get the same item for on Vinted.

The question isn’t whether resale competes with new. It’s whether “buy new” creative can make a convincing case.

Perimenopause is pulling health spending younger

Women as young as 33 are now spending on perimenopause solutions.

On r/AskWomenOver30, symptom management dominates the conversation: hot flushes during client meetings, brain fog at work, products that actually help.

The UK women’s health and beauty supplements market is valued at £1.18bn, growing at 5.7% a year.

Collagen supplements, a closely related category, are growing at 6.27%.

On Reddit, women describe buying fewer products but spending more per item, trading up to professional-grade solutions rather than adding more to the basket. That’s the pattern as people on these forums describe it, not confirmed market data, but it matches a market that’s growing in value faster than in volume.

One in six UK 16-24 year olds is unemployed

The UK 16-24 unemployment rate hit 16.0% in the three months to January 2026.

That’s 731,700 people and the highest rate since 2014.

There are now 3 unemployed young people for every vacancy, up from 1.9 a year ago. The King’s Trust reports6 that seven in ten teenagers wish they weren’t starting their careers in this economic climate. For brands targeting Gen Z, the spending power simply isn’t there for a growing share of this age group.

Closing thoughts

None of this is a prediction. If I could call the next six months with confidence, I’d be running a hedge fund, not an agency.

But there does seem to be a vibe shift going on – even before the war began. There already seems to be anxiety about work, the future, and cost of living, and while these things have for the last few generations impacted those already worse off, today they’re hitting the higher earners.

AI might be intangible, but petrol hitting £2 will not be, or flight routes will not be.

People are still choosing to invest in themselves for now. Health continues to be an area of prioritisation, but done in the right way. It’s strength training and gym memberships over the continual escalation of supplements.

We know inherently how impactful these things are, but we’re not yet seeing it on the spending power. But short of a big shift in direction, I imagine we’re about to start seeing one in the months to come.

This has been fun to put together, and I look forward to reflecting at the start of July to see how right or wrong these things ended up being.

Have a great week

Josh

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.

On measurement

1. ROAS is a vanity metric in a profitability costume.

2. Contribution margin per session tells you more about a DTC brand’s health than ROAS ever will. CM3 = revenue minus cost of goods, minus fulfilment, minus paid media spend.

3. Blended ROAS conceals whether you’re winning or subsidising losses with organic.

4. If you’re optimising for ROAS, you are not optimising for incrementality.

5. MER (marketing efficiency ratio) is blended ROAS with a different name and the same limitations.

On Meta

6. Meta is a scale channel, not an efficiency channel.

7. CTR does not predict CPA.

8. Thumbstop rate does not predict CPA.

9. If you’re not running awareness spend, your conversion campaigns are doing the work of warming cold audiences and paying conversion CPMs to do it.

10. You should evaluate awareness investment after a minimum of three months. Judging it on last-click in week two is a category error.

11. The 45+ demographic is cheaper to reach and often has higher AOV and LTV. Most brands under £5m ignore it because their founders are 28.

12. Logos and CTAs in ads actually perform better on average, which is annoying if you built your whole brand around looking “authentic.”

13. Static ads frequently beat video because the message lands before the thumb moves.

14. The biggest mistake in DPA setup is combining incompatible product sets under one campaign.

15. I’ve seen accounts with 1x campaign, 1x ad set scale to £350k/month.

On creative

16. Jobs-to-be-done research starts not with what people buy, but with what they were doing before they searched.

17. The four forces of progress are: push, pull, anxiety, and habit. The most important two for paid social are anxiety and habit.

18. 1 star reviews are more valuable than 5 star reviews.

19. “I’ve tried everything” is not a customer complaint. It’s a hook.

20. UGC can be scripted. It only fails with bad copywriting or acting.

21. Yappers, talking-head videos of real people just talking, are quietly the top-performing format in several DTC categories.

22. When talking to customers always preface anxieties with “apart from price, what....”

23. Your brand tagline is almost certainly your worst-performing ad headline. Taglines are written for boardrooms, not for the scroll.

24. Review mining at scale is most efficiently done with AI, if you give it the right taxonomy first.

25. Creative fatigue isn’t as simple as many let on. Turn old ads back on. Go on.

26. Testimonial ads work because they remove anxiety rather than add aspiration.

27. “You put olive oil on that?” is a great hook because it assumes knowledge the viewer is compelled to validate. Use your customers’ language.

On strategy

28. Full-funnel advertising lowers CPMs on conversion campaigns. It’s not just brand investment, it’s efficiency investment.

29. At every growth stage, ask: what’s the single constraint that, if removed, unlocks the next order of magnitude?

30. “Diversify away from Meta” is advice given by those who don’t understand most consumer ecom/DTC.

31. Be aware of LTV debt: don’t get to £10m/year with the same LTV you had at £1m.

32. At a certain stage, you have to accept your natural CPA. If it doesn’t work, you don’t have product-market fit.

33. Incrementality testing is the closest thing we have to answering “would these customers have bought anyway?”

34. If your gross margin is under 50%, paid acquisition is extremely difficult to make profitable after fulfilment and media costs.

35. Track profit per employee. It forces you to confront whether each hire is actually driving margin or just making the org chart look right.

On experiments

36. Most creative testing on Meta is flawed because the algorithm redistributes spend within ad sets based on early signals. You’re not testing creative in isolation, you’re testing what Meta chooses to spend on.

37. A creative test needs roughly 20 purchases before you can call a result with any confidence.

38. 80% net new creative, 20% iteration.

39. Media buying experiments need a month, not 5 days.

40. Experiment velocity matters more than confidence per experiment, at early stage especially.

41. Statistical significance is misused in most DTC contexts because sample sizes are too small and observation windows too short.
    

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On AI and what it actually changes

42. AI lets a growth team produce the creative volume of a team three times its size. The advantage isn’t cost reduction, it’s test velocity.

43. AI video works best when it’s either immediately obvious, or not noticeable at all.

44. The gap between “someone who uses AI” and “someone who’s AI-native” is whether AI is the workflow or adjacent to it.

45. Learn to build with AI coding tools now. The growth people who can spin up custom dashboards, scrapers, and analysis tools without waiting for engineering will have a compounding advantage for the next two to three years.

46. AI fluency is a temporary advantage. As tools become easier and more embedded, the differentiator will shift back to judgement, taste, and domain knowledge.

47. “AI-native” will be a redundant phrase by 2028, for the same reason “internet-native business” became redundant. It’ll just be what you are.

On data

48. A blended CPA of £24 means nothing without knowing what the customer bought and whether they came back.

49. Power analysis before an incrementality test tells you whether your test cells are large enough to detect the effect you actually care about.

50. Most “data-driven” decisions in marketing are intuition-driven with data bolted on afterwards.

51. Invest in your data ETL and warehouse.

On category dynamics

52. Health and wellness DTC brands have a structural advantage in creative because pain is a universal hook.

53. Visual DTC (fashion etc) leans into huge volumes of different creator/people so someone can recognise themself somewhere.

54. There are no hard categories, just people who ignore the rules of Meta.

55. If you can get your F&B work DTC alone, then your retail will fly.

56. The 45+ female demographic is the most underserved audience on Meta and often has the highest LTV.

57. Whether you’re dtc or retail-first, don’t add a second sales channel until £5m of revenue.

On the industry

59. The claim that “native beats brand” in creative is true on average, but not exclusively. You need a mix.

60. Video receives roughly 2x the budget of statics across most accounts. Statics often convert better.

61. AI-generated ads are a volume lever, not a creative strategy.

62. The reason most performance agencies don’t evolve into strategy firms is that strategy is harder to sell and slower to prove.

63. The biggest structural shift in DTC since 2020 has been the collapse of reliable last-click attribution as iOS changed everything.
    

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On growth stage

64. From £0 to £1m, the constraint is almost always creative and targeting, finding what works.

65. From £1m to £5m, the constraint shifts to operational capacity and repeatable testing processes.

66. From £5m to £10m, the bottleneck is usually unit economics and whether the model holds at scale.

67. The moment to introduce a full-funnel strategy is when you can see CPMs rising on conversion campaigns without a corresponding CPA improvement.

68. A brand that can’t survive a three-month Meta creative drought doesn’t have a sustainable acquisition model. It has a hot streak.

69. Email and SMS matter most in the £1m to £5m revenue band, where repeat purchase rate determines whether the model is profitable.

On psychology and persuasion

70. Social proof works differently at the top and bottom of funnel. At the top you’re reducing scepticism. At the bottom you’re removing the last reason not to buy.

71. Fear-based creative underperforms in beauty and lifestyle categories where aspiration is the primary purchase driver.

72. Anxiety (one of the four forces of progress) is reduced most effectively in creative by social proof and specificity, not reassurance statements.

73. The “exhaustion arc” customer story works because it validates every previous failed attempt before offering a solution.

74. Reviews from the 45+ demographic convert better because they tend to be specific, context-rich, and written by people who’ve already tried everything else.

On what most people get wrong

75. Most DTC founders underinvest in creative volume and overinvest in creative polish.

76. Most performance agencies optimise for reported ROAS because it’s easier to present than contribution margin.

77. Most creative testing is actually budget testing masquerading as creative testing.

78. Most retention strategies are just email sequences with a better subject line. Not a repeat purchase model.

79. Most people who claim to understand LTV don’t understand the margin at which that LTV was generated.

80. Most agency pitches fail because they answer “why us” instead of “why now, and why does this matter to you specifically.”

On what almost nobody knows

81. Cost per reach going up while CVR also goes up is not a contradiction. It means Meta is spending into higher-value audiences.

82. A brand with a 3.5x ROAS might be losing money on every customer if COGS, fulfilment, and variable costs are high enough.

83. The incrementality of branded search is lower than most brands assume. Many of those clicks would have happened anyway. Assume it’s 0.1x.

84. “Meta’s algorithm has gotten smarter” usually means “we got better at brief writing and structure.” The credit rarely belongs entirely to the platform.

85. The measurement problem that MMM still can’t solve well is real-time responsiveness. It’s a retrospective tool used as a planning tool.

On writing and content

86. The most shared pieces of content make the reader feel smart, not informed, smart.

87. Contrarian takes work best when the conventional wisdom you’re attacking is genuinely prevalent, not a straw man.

88. The difference between Grade 7 writing and Grade 12 writing is that Grade 7 says what it means on the first read.

89. The best hook for a founder-vulnerability post opens in the middle of the failure, not with context.

90. The best Substack growth lever is not frequency. It’s having a clear reason to exist that nobody else fills.

On how growth teams work in 2026

91. Every growth team is now somewhere on a spectrum from “we use AI occasionally” to “we wouldn’t function without it.” The gap is widening fast.

92. The growth team that treats creative as a hypothesis rather than a deliverable will outpace the one that treats it as a production output.

93. “Move fast and break things” was a software company mantra applied to marketing by people who didn’t understand the difference. You can’t A/B test a brand perception.

94. The thing most growth teams under-budget for is time to think. The calendar fills with execution and the strategy atrophies.

On how consumer brands work in 2026

95. The brands that tried to be “authentic” by mimicking UGC without the actual user part have mostly been found out.

96. Founder-led content performs better than brand content for most sub-£20m DTC companies. Not because it’s personal, but because it’s legible, you know who’s speaking.

97. Most brands building “communities” are actually building email lists with extra steps.

98. The Dyson problem: great product, brutal creative. The reverse exists too. Creative that oversells a product is worse than creative that undersells it, because the reviews will eventually kill you.

99. The brands winning on TikTok in 2026 are mostly winning because someone in the building is genuinely interested in making content, not because they cracked an algorithm.

On what it actually feels like to work in growth right now

100. The feeling of having a great creative test result land on a Friday is still one of the best things about this job. It hasn’t been automated yet.

101. The worst thing about performance marketing culture is the tendency to confuse busyness with rigour.

102. Lean is the new default, and that’s going to require a mindset shift for psychological comfort.

103. The most underrated skill in growth is writing. Not copywriting. Writing, the ability to explain what you’re doing and why to someone who isn’t in the room.

104. The growth meeting that never ends is the one where nobody has established what decision needs to be made by the end of it.

105. Context switching is the new norm, and AI only accelerates that.
     

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On the agency relationship

106. The best agencies act like lawyers, not yes people

107. At the moment AI hasn’t helped with cost.

108. Your agency should challenge your thinking all the time.

109. Agencies get you access to usually over £1m of head count per account. That’s irreplaceable in-house.

On the craft

109. Writing a brief forces you to know whether you actually understand the customer. If you can’t write it, you don’t.

110. Best practice” in performance marketing has a shorter half-life than most people admit. What worked in 2025 is often actively wrong in 2026.

111. Spending two hours doing customer interviews is usually worth more than any AI assisted research.

On things that are genuinely changing in 2026

113. Creative production that used to take a week now takes a day. The time saved is not being reinvested in thinking, in most teams.

114. Incrementality is finally getting the attention it always deserved.

115. The post-cookie world turned out to be fine for everyone who wasn’t entirely dependent on third-party data. That group was larger than expected.

116. Growth people are becoming engineers.

117. The brands winning on YouTube in 2026 figured out that long attention and short attention require fundamentally different creative approaches, and stopped applying the same creative to both.

118. Subscription models in DTC turned out to be harder than they looked when every brand launched one in 2020-2022. The ones that work have genuine habitual use cases.

119. Some brands are realising they have audiences, not communities, and that’s fine.

On things that haven’t changed

120. Meta advertising is advertising.

121. Advertising has to sell.

122. Simplicity beats complexity.

123. Operating at 100% capacity creates a fragile business, build in space to crack.
     

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On the wider world that growth operates in

124. The cost of living crisis changed consumer behaviour more than most teams have updated their models to reflect.

125. The brands winning in grocery and everyday essentials are the ones that made the implicit trade-off explicit: this is cheaper, or this is better, pick one.

126. The environmental claims conversation has become complicated enough that most brands have quietly retreated from it. The ones with genuine credentials now have more white space.

127. Gen Z’s relationship with brands is not what most brand strategists predicted. They’re not inherently anti-brand. They’re just better at detecting nonsense.

128. The resurgence of in-person retail is real and most DTC brands still treat it as secondary. The ones blending both well are building the most defensible positions.

129. Social commerce is still not quite the thing it kept being predicted to be in the UK. The infrastructure isn’t there yet.

130. The creator economy has matured. The hobbyists have mostly dropped out. What’s left is more professional, more expensive, and more effective when briefed well.

131. Economic uncertainty has lengthened consumer consideration cycles in discretionary categories. Most brands haven’t updated their channel mix to reflect this.

On the culture around the job

132. Most growth Twitter/X is people restating what worked for them as universal law. Read it, but hold it loosely.

133. “Founder mode” became a phrase that was used to justify almost anything. The useful version of it is simple: stay close to the work.

134. The tendency of growth people to dress up industry gossip as market insight is a known failure mode. Name the pattern so you can catch yourself doing it.

And finally

135. The best DTC brand you know is probably one you heard about from a friend, not an ad. That’s still the industry’s most important unsolved problem.

136. The teams that ran the best experiments in the last year are the ones that wrote down what they expected to happen before they ran them.

137. The best briefs are written in the customer’s language, not the strategist’s.

138. Every successful DTC brand has a moment when a single creative unlocked scale. The lesson is not to try to recreate that creative. It’s to build the system that finds it again.

139. The teams most resistant to AI adoption are often the most skilled at their current way of working. Capability and change readiness are different things. This is the individual’s version of the Innovator’s Dilemma.

140. The growth industry in 2026 is better at measurement, better at structure, and still not great at the thing that actually drives results: making things people find interesting.

141. The question a founder should ask before hiring any performance agency: “Can you show me a client where you improved margin, not just ROAS?”

142. The question that reveals more about a brand’s health than any dashboard: “What’s your repeat purchase rate at 90 days?”

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Last week, we were away on our company offsite as we embarked on the journey to become AI-native. The current goal state is:

For any task, can it first of all be given to AI to complete for you

I take the David William Silva view that LLMs likely won’t be the singularity answer. There is just too much devolving to the baseline and average involved in them. Getting exceptional results from AI today really requires exceptional expertise.

That’s not to undermine their power – on the contrary, that is their power. But understanding how to maximise it is the game. And that for us at Ballpoint is what this next quarter is about: let’s go as close to 100% AI as possible, so we can understand explicitly where the LLMs help us the most and where our position and view is tantamount.

Amongst all of this, the concept of taste keeps returning.

I imagine a world one day into the future where we have weekly internal seminars reviewing essays of note that help deepen our thinking. I imagine an apprenticeship approach to learning.

On one of the cooking shows once, I heard a Michelin star chef say that in their kitchen you’d spend days and days and days learning how to slice an onion. And until you had become an expert at it, you couldn’t advance beyond it. I’m sure there will be approaches to learning skills that reflect that.

Our offsite last week was day zero of this journey. Everyone spent two days in the command line and cursor. The excellent Leo Ubbiali led our primary session: getting everyone in best practice mode. And then my friend and ex-colleague Paul Connor talked us through how AI has empowered his side projects, including new game Phrazy.

I hope you enjoy your long weekends.

Josh

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Key image of the week

Signals

Key signals for builders, growers, and operators.

• Meta launches Adaptive Ranking Model (ARM) [Meta Ads] – Meta upgraded its ads algorithm this week with tests in Q4 showing 3% improvements to conversions. This adds ‘LLM-level complexity’ to the ads algo to better serve more relevant ads.

• Meta launches its Ranking Engineer Agent [Meta Ads] – this doubles model accuracy and improves rollout speed of ad model tests. This ‘compresses weeks of manual work into hours.’

• Trialling new Meta features [Meta Ads] – we’ve been testing Meta’s new creative testing tool, as well as flexible ads for a while – and this week shared learnings from them. Key one: Flexible Ads proved to be 2x worse CPA than equivalent ads in ad set tests.

• Oracle laid off 30,000 employees [AI] – joining big changes across Block, Meta, Amazon and more this year.

• Claude’s codebase got leaked on Tuesday [AI] – sparking a big discussion about unreleased features. ‘Buddy’ their own tamagotchi seems to have been released overnight.

The Stack

A shortlist of stuff I recommend you read and watch this weekend.

📝 Your marriage has a third. After Babel
📺 The Thinking Game Documentary on Demis Hassabis. YouTube
📝 The robot training for the Olympics. Digital Native
📝 Facts and fights for the moral high ground. Behavioural Scientist
📝 World models. Not Boring
🎧 What is Twitter’s legacy, 20 years later?. The Atlantic
📝 Cryptos true believers demand to be taken seriously. Vanity Fair

What do you think?

Please leave feedback and a comment on the format. This is a newly launched feature this year and we’re always looking to improve. If you like it, hit reply, leave a comment, like us on substack, forward to a friend and all other needy call to action requests you can usually expect at the end of these posts.

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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 seen yet.

Late last year, Meta started testing a ‘creative testing tool’ where you can launch five ads inside an ad set without disrupting learning. Five ads for most accounts is limited, but when in conjunction with the creative testing tool, it’s potentially a way to run accounts.

We’ve been testing these for the last few months across a series of our accounts. We’ve done a mixture of isolated AB tests as well as before and after experiments.

Here’s what we’ve learnt so far this year, and what we’re going to be doing with it.

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Flexible ad units: the promise vs the reality

The beginning of last year, we won an early-stage client who had one singular flexible ad that was working. It contained 10 separate, distinctly different ads within it.

One of the first moves we made was to move away from the flexible ad unit.

Our methodology is strongly rooted in creative testing, learning and iteration. We are intentional about creative tests, approach them strategically, and use every week’s experiment to inform follow-ons.

So for us, flexible ad units remove information that allows us to learn.

With that client, we were never able to find product-channel fit for the client. We eventually re-tested the flexible ad unit in case there was some magic in the delivery of it itself, but it never rebounded. For a long time we were confident in our decision.

Then late last year (2025), I saw rumblings on X about the unit. Some media buyers were claiming strong performance from these units over and above typical setups. The 99th percentile Consolidationists would argue that the more diversity you can fit into individual units the better. And lots of belated-Andromeda hype all pointed to the valuelessness of variants within individual units.

Throw into the mix the new creative testing tool, and it felt like it was time to revisit.

We started running a series of tests. Some before/after, and then a couple of stricter tests.

Flexible ad units: A/B test results

We ran two isolated AB tests using Meta’s testing tool. In each example, we ran the same setup.

• BAU contained 3-5 variants of an ad

• Flex ads contained a single ad unit with each of those variants within it

We ran this for a week.

The outcome in both tests was stark: the flexible ad unit variant ran at double the CPA of our BAU.

This was an annoying one for us. Had the flex unit won, this would have hugely increased our capacity for ad volume in a consolidated way.

As it stands, we have two very similar test results. With anecdotal before and after results showing similar things.

Summary: we’re derprioritising flexible ad units

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Meta’s creative testing tool: good for the wrong reasons

The other tool, which we first ran tests on in October 2025, is different.

The concept here is that you can run creative testing inside your main hero campaign and ad set, rather than inside a separate setup.

Most accounts these days are running some form of setup that encompasses: (1) dedicated testing, (2) scale/bau/hero setup. We are the same.

This new tool means being able to test inside those heroes without disrupting performance.

You force spend into them, and at the end of the tests, they can then scale.

The logic here is good: you get benefit of not having to disrupt something that’s working, and they build data in the place where they will live.

These have limits. You’re capped at five launches per week, which given we like to variant test still, means that we’re limited by what we can launch.

We’ve been testing this now in a series of accounts. Here’s what we’ve found.

Test-week performance is misleading

During the test week, almost every concept looks like a loser. CPAs during the learning phase were consistently 20-60% higher than the business-as-usual benchmark.

Depending on client stage, we expect to see a 20-40% win rate defined as concepts producing CPAs that are the same or better than the account average.

In these tests, no launches saw winning ads. Now an individual week doesn’t prove anything, nor does a single client experience. But we have now looked at this across a series of accounts, as well as across multiple weeks. Repeatedly we see the same things, win rate is about 6% rather than the usual 20-40%.

Note: we’ve not run explicit AB tests here where we ran usual creative testing structure alongside this setup. Given complexity and cost of isolating that test with audiences, we opted against it in favour of faster learning.

If you treated these on the test-week alone, we’d have binned all the ads.

But we decided to keep ads live to see what would happen afterwards, and this is where it got really interesting.

Post-test-week performance improved almost across the board.

One ad that had 60% higher CPA during test week graduated and had a CPA 40% below the account average.

Not only was the test week not a good indicator for CPA, nor did it indicate what would happen with scale.

Here was activity from one campaign we saw.

Note: numbers have been anonymised but % differences remain the same.

During test week, Concept A was one of the rare concepts that beat the test setup.

B,C, and D were all higher and what we would have deemed fails.

And yet in the post-test period, we saw:

• Concept A scale with better CPA than the account, as we would hope for such a definitive winner.

• Concept D, previously a marginal loser, scaled to about half of Concept A’s growth, but with an improving CPA.

• Concepts B and C both remained fails, and were ads we ended up turning off.

In other account tests, we saw more results like concept D: those with CPAs that were higher than account CPAs, which in usual structures we’d deem losers, becoming winners afterwards.

Creative testing tool is great for forcing spend

Our takeaway when we’ve round up internally is that the creative testing tool isn’t an effective way to test creative, but it is an effective way to force spend and give ads a head start in a hero campaign.

And so there are instances now where we’re looking to use this setup with this in mind.

A few examples:

1. Where overall account spend is low and running isolated tests is expensive

2. Accounts with high CPA where we use less correlative higher funnel events for testing, as a means of getting spend into a conversion-asset

3. Instances where certain ad sets have high spending, low performing ads that just can’t be shaken

The testing tool itself still helps identify rocketships – they seem to win regardless – but the lions share of winners don’t get picked up.

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Meta update: March 2026 – push delivery to an ad

As I write this (Friday 27th), Meta has this week rolled out a new feature allowing you to force spend to individual ads inside the hero.

Our current state with creative testing tool is essentially a way to force spend into a hero campaign to new assets before we see how they truly behave.

With this new launch in mind, it’s likely we’ll use the creative testing tool less and instead move to this new feature.

We are rolling out tests across the agency over the next two weeks and will be testing a variety of setups. Key things we want to understand:

• How much spend to force in

• Whether ads should be tested first

• Does this differ depending on creative testing method

If you’ve been playing with the new tool, I’d love to understand your setups.

Leave a comment as I’d love to hear how you’ve been finding these features.

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Josh Lachkovic is the founder of Ballpoint, a creative growth agency for DTC and ecommerce brands. Subscribe to Early Stage Growth for weekly insights on growth, creative strategy, and experimentation.

I’m testing times we deliver this weekly aggregate roundup. Let me know what you think of the Saturday delivery.

Context and experience are becoming the most valuable skills in AI.

But something else we all need to learn is perseverance.

If you tell Claude to connect to an Ads MCP and ask it for recommendations, it’s going to tell you to increase brand search because of the mega ROAS. There are those who see that as a sign of AI’s failure and stop.

If you prompt Nano Banana with a basic prompt, you get something OK but still looks like AI. But if you spend eight hours refining, you’ll produce something lifelike.

It takes work to keep trying.

People who play video games know this. They know the feeling of relentless repeating the same thing over and over, getting more and more frustrated only to finally have a breakthrough.

Software engineers know this. Problem-solvers know this. Big problems require so much work that is essentially failing over and over. And we need to persevere through it.

And AI is that challenge writ large.

As it currently stands, AI is pretty bad at replacing like for like work. Yes you can get 80% of a result in 1/10th of the time. But that last 20% is where all the value in the world is created.

But what AI is exceptional at is, with the same level of input time, your output scales 10x more.

It’s not ‘turning an 8 hour task into 1 hour’ it’s ‘if I used those same 8 hours, I can do the job of 100 hours.’

But getting there requires perseverance.

I hope you have a great weekend.

Josh

Key stat

Signals

Key signals for builders, growers, and operators.

• Meta had a large outage on Monday [Meta Ads] – The X rumourmill is putting it down to Meta rolling out its new attribution system. One of the reported problems was huge overspends in cost controlled campaigns. We’re not seeing it too much in our (mostly UK-centric accounts), but keep an eye out.

• How to diagnose any growth problem [growth] – I shared my framework this week for how I diagnose growth problems and prioritise them with a revision on the old ICE framework.

• Playwright CLI version is way more token efficient [AI] – many of us are already using playwright instead of the default claude code browsing function, but I recommend an upgrade to the playwright CLI version. This is considerably more token efficient in most use cases.

• Meta is adding a 2% tax on UK ad spend [Meta Ads] – for every UK advertiser, you’re about to see Meta CAC go up by 2%. They’re adding taxes across Europe related to taxes being bestowed on them. Update your financial plans soon.

The Stack

A shortlist of stuff I recommend you read and watch this weekend.

📝 The Science of why AI still can’t write like you. Every
📝 It’s strictly business: the enduring allure of mafiosi in culture. Economist (£)
📝 Don’t make a meal out of your business lunch. Monocle
📝 Is Britain ready for US-style religious politics? FT (£)
📝 An Interview with Nvidia CEO Jensen Huang About Accelerated Computing. Stratechery
📝 The salaries of 60 New Yorkers. New York Magazine (£)
🎧 Outliers: JW Marriott: Building an empire without a master plan. Farnham Street

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It usually happens like this: performance has gradually been heading in the wrong direction. First, you rightly ignore it as these things usually work themselves out. Then it starts to become a trend but you still allow it. And finally, it becomes something you need to pay attention to.

At this point, the usual run of experiments won’t cut it.

I re-read Ben Horowitz’ A Hard Thing About Hard Things last November and one of the best chapters remains Peacetime vs Wartime (I wrote about wartime before product-market fit three years ago).

What I’ve come to realise is growth fits into these two modes of peacetime and wartime as well.

Wartime growth is when you don’t have performance in the right place
Wartime growth is not having product channel fit 
Wartime growth is not having product market fit
Wartime growth is not finding marginal sales as you scale
Wartime growth is being unsure that your ads are actually delivering sales
Wartime growth is not breaking even in time for your cash flow – or ever
Wartime growth means your creative win rate is 5-10%
Wartime growth means brand guidelines must be ignored
Wartime growth you are holding spend flat while you figure things out
Wartime growth is trading off no statistical significance for big bets
Wartime growth is maniacal focus on getting CPA to a good place
Wartime growth is not having marketing calendars
Wartime growth is wholesale landing page swapping

Peacetime growth is when you are scaling
Peacetime growth is about relentless creative operations scaling
Peacetime growth is having a Job Story and angle that *works*
Peacetime growth is 80% finding new concepts to demonstrate that core JTBD
Peacetime growth is loosening efficiency so you can scale hard
Peacetime growth is aiming to triple spend in six months
Peacetime growth is measuring all creative by £ spent on it
Peacetime growth is allowing room for brand consistency and design
Peacetime growth is small, incremental CRO experiments
Peacetime growth is statistically sound data

• When you’re in peacetime, experimentation is how you grow.

• When you’re in wartime, experimentation is how you survive.

Every business starts in wartime, then if you’re lucky, you have some period of peacetime until inevitably you fall back into wartime again. And the cycle continues.

I’ve previously described these as ceilings and growth spurts in an S curve. But I’ve grown to realise a ceiling feels too gentle; these are cycles of peace and war.

Experimentation is always urgent because no matter what state you are in, it’s the way out. But during wartime, it requires that you go back to the drawing board and begin with first principles.

I write twice weekly here every week. This is the weekly Tuesday essay: a key learning from my 16 years experience growing consumer businesses. Every Friday is a weekend debrief: key stories, stats, and reads for the weekend.

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Diagnosing problems during wartime

I was auditing an account recently for a brand spending about £3m a year. During the early sales calls they mentioned who their target customer was the 50+ female. Hallelujah I thought.

The 50+ female is the holy grail for advertisers. The 50+ female still uses social, she over-indexes as a Facebook user (a platform still underserved compared to IG). She is both rich and part of a high earning household. And she’s the primary shopper.

But as we got into the account I pulled the breakdowns. (Sidebar, I can’t believe Meta still give us breakdowns, use them while you can).

2026, year to date, 35-44 is the biggest demo for spend, reach and purchases and not by a small amount either. Yes there’s a female skew, but it’s pretty marginal.

We extended the search back further and looking at the monthly trend saw their 55+ demo halve from 40% of spend to less than 20% over the course of 18 months.

We’re no longer in peacetime.

So what does experimenting in war look like?

Begin with my Hypothesis Matrix to analyse why something changed

A while back, I came up with a simple matrix for diagnosing big changes in performance.

It’s a two-by-two grid with Location along the x axis (External / Internal) and then Ownability on the y axis (Ownable / Out of our hands).

Key question above this grid – “Why has the audience shifted?”

In the external and out of our hands, I wrote down:

• Tax / budget concerns

• Less FB usage in category

• Meta algorithm shift

In external but ownable, I wrote:

• New competitors

• Run out of customers

• Shift in social media trends meaning creative no longer works

• Shift in social usage to different placements

In external and on the border I put:

• Culture shifts away from product category

In internal and out of our hands, I put:

• Price increases last year

In internal and ownable, I wrote:

• Creative

• Campaign setup

• Any brand changes, rebrand, redesign etc (?)

• Landing page / website changes (?)

• Messaging changes (?)

• Email onboarding flows (?)

In the early days of my career I was in a meeting one August when someone offered up “it’s summer” as an answer to why performance was down. Said colleague was quickly dressed down by the CEO for using the external factor.

That stayed with me ever since. The tone was obviously curt, but beneath it was an important message. The mindset of diagnosing problems should always start within.

And so whenever I fill in my Hypothesis Matrix, I always start with the top-right: internal and ownable. And while I do also write down client-side changes in that quadrant, I always begin by listing out stuff that we, Ballpoint, own first of all.

Under creative, we can start digging even deeper.

Is it because we’ve stopped producing a certain visual hook? Or maybe all of our videos have switched to 15 seconds whereas this audience likes 45? Have we changed the type of creators we use? And so on and so on.

Once I’ve got my initial draft done, I’ll go to the client and ask for what they think it could be. I’ll begin by talking through the Ballpoint-ownable hypotheses we have, before going into some examples of others we had.

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Data gathering and experimentation

Now, we switch into the next phase: data gathering and experimentation.

Another peacetime/wartime distinction:

In peacetime, getting insights and gathering data is usually about finding extensions of what you know. You might dig through Reddit to unearth a new framing of your problem. Or maybe a customer interview revealed a slightly different catalyst for your Job Story.

In wartime, you need to go deeper.

Every hypothesis on the matrix requires some digging.

At this point, you need to apply pressure and fast. You don’t have time to analyse everything. Fortunately with Claude, much of this data is quicker to get than it was a year ago. But still, there is such a thing as too much data.

Example data explorations

Back in Jan, we saw damp performance in some accounts. I blogged about some of those findings, in particular that health behaviours had changed significantly this year. Dry Jan isn’t a thing now, protein for women is on the rise, and we’re moving towards strength over skinniness as the ultimate in high status.

We might explore if competitors have started using big influencers or launched a TV campaign, or perhaps they’ve launched an offer that’s just dominating.

We dig deep enough to form mini-hypotheses at an experiment level. And then we begin creating experiments around those ideas.

Prioritising experiments with Impact-Probability (IP) and Expected Value (EV)

At this stage, I like to evaluate expected values using our Impact-Probability (IP) framework. This is a simplified version of the infamous ICE frameworks.

1. Impact is the degree that change could shift your problem

2. Probability is what % likelihood you have that result will happen.

Let’s say your core metric you optimise towards is contribution margin.

Impact you should define as what potential uplift that would have in CM next month.

Let’s imagine one experiment hypothesis means you could double your conversion rate meaning based on next month’s forecast you increase contribution margin by £250k.

But the probability of that happening sits at 20%. This puts the expected value of said experiment is £50k.

Expected value (EV) = Forecast uplift in key metric * Probability of event occurring

Maybe you’ve got another experiment you’re debating running which can only generate £75k of CM gains but you’ve got 80% probability of success.

• EXP01 EV = £50k

• EXP02 EV = £60k

Start with number 2.

The last resort: owning the unownable

In grave situations, you may well exhaust all of the lovely top-right quadrant of ownable and internal problems.

It’s at times like this that you usually need a total strategy reset. Perhaps your core customer has really radically changed. Maybe you’re selling wine to an age bracket that thanks to a really big influential movement has gone 15% teetotal.

Out of our hands ideas can become ownable with a strategy shift.

And you can turn external factors into internal ones with a revolution as well.

But these changes don’t come cheap.

I hope you’ve found this useful.

I love experimentation. It’s one of our founding philosophies at Ballpoint. But it’s taken three years to identify these two distinct states of business. There is wartime and peacetime growth. And the model for experimentation during those phases is entirely different.

If you want help pinpointing whether you’re in wartime or peacetime, then drop me a line. Or better yet, start a discussion in the comments below.

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I’m building Ballpoint: the growth agency I always wanted to hire when I was a DTC founder and before that a head of growth. We have scale brands from £1m → £50m through digital advertising. If you’re looking for support, then you can email me on josh@weareballpoint.com.

In the meantime, if you enjoyed this please consider giving it a like, a comment or forwarding it to a friend.

In SF, AI billboards were everywhere. As well as making it seem like the entire economy there was AI-focused, it also acted as a good reminder of forgotten launches.

Even brands we’ve already signed up for, we forget about quickly. If your product use isn’t daily or weekly at worst, then you risk being forgotten. If your product frequency is monthly or less, then you need constant ways to remain front of mind.

I’ve written about LTV debt in the past, the notion that brands invest so heavily in acquisition that they end up with an unbalance on the other side of the fence. I’ve seen firsthand brands who have managed to nail an acquisition engine – scale spend from £50k/month to £2m, but their LTV profiles remain static.

With the AI billboards this is about something even more dangerous: users churning before they’ve even experienced value.

With potential launch velocity now at 100x what it was before, I feel that activation marketing and advertising will become even more prominent. An acquired user will mean less and less, and with some of the AI CACs I’ve seen that feels pretty dangerous.

I hope you have a great weekend, please share feedback and vibes.

Josh

Key stat

Signals

Key signals for builders, growers, and operators.

• Meta changes link-based attribution [Meta Ads] – Until now a “linkclick” on Meta also meant a like or a comment or many other platform-level engagements. That’s changing with a link meaning an outbound click. For anyone who does click-only attribution, expect a bit of a shift. Some studies have shown that likes and comments and saves are actually more impactful for revenue than clicks, so be aware.

• Meta is reportedly banning accounts for using Claude MCP [Meta/AI] - many reports emerged this week on X that accounts are being banned for connecting to Meta via the various MCP servers out there. People inside MCP providers are denying the allegations, but it has certainly spooked many people. A Meta account ban is hard to come back from without account support, so we recommend caution.

• Authenticity and provenance are out, function and lifestyle are in [consumer] – this was my main takeaway when comparing UK and US retail over the last few weeks. As ever US Retail remains miles ahead of UK, though we are catching up.

The Stack

A shortlist of stuff I recommend you read and watch this weekend.

📝 Nobody gets promoted for simplicity. Terrible Software
📝 Everybody loses. Vulture (£)
📝 The science of why AI still can’t write like you. Every
📝 How TV learnt to sell itself. Works in Progress
📝 Are we in a smut renaissance? New York Times (£)
🎧 The business of Formula 1. Acquired
📺 Mad Men Revisited: 10 Year Anniversary with Jon Hamm & John Slattery

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As with my last visit, I was blown away by the volume of new, challenger brands in US retail. In the UK, we see the ‘posher’ supermarkets take bets on small indies. And there are maybe half a dozen excellent but tiny shops in London that stock almost exclusively challenger brands. But our shelves might still be 80% big Consumer, and 20% shared between half a dozen entrants in each category.

The US is a different beast altogether. Go into Erewhon, and it’s the size of our supermarkets with the selection of our tiniest independents. Whole Foods shares shelf space with Big Consumer and small indies. But even your typical neighbourhood grocery store stocks a strong selection of up and coming challenger brands.

I’ve visited the US four times in the last four years, and this only seems to be accelerating. It was while I was in the US this time, however, that this all started to signal something else: slowly, somewhere, we’ve seen the death of the hipster.

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What is a hipster?

In 2007, Christian Lorentzen wrote in Time Out New York that

”hipsterism fetishizes the authentic”

Hipster has had many definitions over the years. In the UK in the mid-2000s, it was used interchangeably to describe a cross section of music scene kids (indie, rock, punk). Later it was heavily associated with handlebar moustaches, coffee-drinkers and cyclists. And by proxy of where they associate (Shoreditch, Williamsburg), for a while it was a proxy for the pejorative ‘gentrifier.’

Hipster didn’t begin with Lorentzen. Its earliest etymology goes back to the 1940s jazz scene, through Norman Mailer’s 1957 essay “The White Negro” and into the counterculture that followed. But it’s the ‘pursuit of the authentic’ that is the definition I’ve always returned to.

I think about a couple of relative shopping experiences between London and Los Angeles.

In Los Feliz, LA, I visited a shop called ‘General Store’. We have a ‘General Store’ in Peckham, LDN too and so we went to see how they compared.

Our Peckham General Store sells great coffee, locally made sourdough and fresh pastries, wild garlic foraged in the rural home counties, fruit and veg via Natoora but with the implication of being direct-from-farmer. It stocks a tiny selection of natural wines, and a very curated selection of brands.

The brands it stocks are all intentional. The merchandising policy seems to be:

• never stock more than one or two products per category,

• never stock brands that are available on the mass market,

• only stock brands that come from specific locations where that product is seen as the best

You might for example have a type of nougat from a very specific village in Tuscany.

In many respects, this is our hipster pursuit of the authentic.

Los Feliz General Store shared some initial similarities. Head in and the smell of great coffee, and fresh, locally sourced pastries fills the air as well. But this is where the similarities end.

Los Feliz General Store now stocks dozens if not hundreds of new, independent challenger brands. Some, like DTC darling Grüns, I recognise, but the vast, vast majority are all new to me.

I’m like a kid in a candy store and want to try so many of these products. Gummies for every ailment, candles which promise to bring the scent of California home with me, aftershave brands that ooze cool, protein in all manner of forms.

And the selection in this General Store, like the London equivalent, is at the narrower end of the spectrum. 10 minutes down the road in Erewhon, and there’s half a dozen choices of creatine to choose from, another dozen multi-vitamins, crackers and chocolates that depending on your need come packed full of protein, fibre, or carbohydrates, and 30+ different waters.

I’m reminded of a conversation I had with an angel investor when I was running my last business Wine List. We were an education wine play where the typical desired outcome was our consumer would understand wine a bit better and begin their own ‘wine journey.’ It was Lorentzen’s Hipster by definition. What better way to pursue the authentic than find individual winemakers who have made something that tastes uniquely of their own land?

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Said angel investor recommended I build a wine DTC: try and build the definable wine brand for the future generations, like how Jacob’s Creek or 19 Crimes had beforehand. If you get that right, that’s one of the few ways to make a lot of money in wine, but it was a completely different game to the one we were playing.

Some of the UK-US differences are innate cultural ones. The UK remains a country default-cynical towards consumerism.

But in many ways, lots of US culture eventually finds its way to the UK market. And so when I look at the breadth of brands that the US has on offer, I imagine we will one day share at least some of that breadth as well.

Part of why this shift has happened is practical. DTC and social media have made it radically cheaper to launch a brand. You no longer need a decade of trade distribution to earn shelf space. But I think the deeper reason is that the consumer has changed. The generation buying these products doesn’t find identity in provenance the way an earlier cohort did. They find it in optimisation, in function, in lifestyle as a project. We now find brand identity in creatine, rather than PDO tomatoes.

And maybe that’s the real death knell for the hipster. From San Francisco to Los Angeles, the bougie independent shopper is no longer pursuing the authentic. They’re pursuing what works, what’s new, what fits the life they’re building. Functional lifestyle is the new hipster, and the shelf space proves it.

For challenger brands, particularly UK ones looking at the US market, this matters. Origin stories and craft credentials are at best the minimum entry requirement, and by no means a USP.

Function and lifestyle are key. Strong visual identity that stands out and resonates is vital.

These are observations, not conclusions. The US is further along this curve than we are, and the UK’s natural scepticism towards consumerism means it won’t land here in the same way. But the direction of travel seems clear. If you’re building a brand in the UK and planning to scale, it’s worth asking: are you still selling the authentic, or are you selling the functional? Because the American consumer already knows which one they’re reaching for.

I’m building Ballpoint: the growth agency I always wanted to hire when I was a DTC founder and before that a head of growth. We have scale brands from £1m → £50m through digital advertising. If you’re looking for support, then you can email me on josh@weareballpoint.com.

In the meantime, if you enjoyed this please consider giving it a like, a comment or forwarding it to a friend.

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I’m Mark, Ballpoint’s new Head of Creative Strategy. My background is as a copywriter (and I basically still think that’s what I am). But something strange has been happening to me at work recently.

A good chunk of my week is spent writing creative briefs for our clients. Once signed off, they are then passed onto graphic designers or video editors who turn my ideas and copy into finished ads. The whole process generally takes a few days.

One important piece of these creative briefs is the visual reference: pictures or videos or other ads that demonstrate the kind of thing I had in mind. It can take me ages to find one that I’m happy with, so I started using AI to make little mockups instead. I made sure to label these as “rough” and “for reference only” so nobody got confused.

Then I started seeing some of my mockups popping up on Instagram. Our creative studio had decided that they were good enough to work with after a few tweaks.

What does this mean? Have I transcended strategy? Am I “full stack”? One thing that is for sure is that my design skills haven’t improved. The tools have just got good enough to make that irrelevant.

It does feel like the bottleneck in creative is shifting from production to thinking. Soon, the hardest part won’t be making the ad; it will be knowing which ad to make and why. None of which is to say that designers and editors become less valuable. If anything, when anyone can produce something passable, teams who can produce something excellent matter more than ever.

Anyway, here’s what caught our eye this week.

Key Stat

Signals

Key signals for builders, growers, and operators.

• Meta embeds Manus into Ads Manager [Meta Ads / AI] – Meta’s $2bn AI agent acquisition is now being quietly rolled out into Ads Manager. Unlike tools that just make suggestions, Manus executes multi-step tasks like campaign analysis, creative briefs and performance reports, all with minimal human direction. Worth watching closely.

• Agency headcount is falling (and AI hasn’t even landed yet) [Industry / AI] – The IPA’s annual Agency Census: open roles down 41%, graduate recruitment down 56%. As Josh wrote in this week’s essay on becoming AI-native, the cuts are happening in anticipation of AI, not because of it.

• We appear to have hit peak Greggs [Consumer] –Total sales rose 6.8% to £2.15bn but pre-tax profit fell to £167m, with like-for-like growth slowing to just 1.6% in early 2026. Shares are down 25% in a year, partly on fears that GLP-1 drugs are killing demand for sausage rolls. If the UK’s most beloved value brand is feeling it, it says something about where the consumer is right now.

The Stack

A shortlist of stuff I recommend you read and watch this weekend.

📝 The tension between scale and discretion. The Stanza (£)
📝 The death of Spotify: Why Streaming is Minutes Away From Being Obsolete. The Artist Economy
📺 5 OpenClaw agents run my home, finances, and code. Jesse Genet
📝 How De-Yan is shaping the future of brand experience. Creative Review (£)
📝 The Data Centers Have Arrived at the Edge of the Arctic Circle. Wired (£)
📝 Chupa Chups ‘final boss’ in new wrapper launch. Creative Review (£)
📝 What It Takes to Make Good Decisions: Judgment, Not Calculation. Behavioural Scientist

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“The way I interact with a computer has completely changed forever.”
– Mark Holland, our Head of Creative Strategy

Something changed over the last month. I and another colleague have become AI-native.

My colleague Mark, our head of creative strategy, told the team at Friday Beers & Cheers “the way I interact with a computer has completely changed forever.”

As soon as he said it I realised it was the framing I’d been mulling on for a week or two.

It’s statements like this that start to turn heads away. You risk sounding like a hype merchant or a peddler of NFTs. But this time it does feel true.

By this stage I’ve heard a lot of people reference Matt Shumer’s essay Something Big Is Happening1. The intro lands the plane:

Think back to February 2020.

If you were paying close attention, you might have noticed a few people talking about a virus spreading overseas. But most of us weren’t paying close attention. The stock market was doing great, your kids were in school, you were going to restaurants and shaking hands and planning trips. If someone told you they were stockpiling toilet paper you would have thought they’d been spending too much time on a weird corner of the internet. Then, over the course of about three weeks, the entire world changed. Your office closed, your kids came home, and life rearranged itself into something you wouldn’t have believed if you’d described it to yourself a month earlier.

I think we’re in the “this seems overblown” phase of something much, much bigger than Covid.

This is a bit of a longer read (12 minutes or so) than usual and so am giving you a bit of a breakdown of what to expect here:

• The job market today

  • Defining AI native

• I think we’re months away from AI being able to do most of our work

  • Creating a handover podcast for a client

  • Identifying product focus based on retention, LTV and cross-sells

• The new skills we need to learn

  • Taste, multi-disciplinary learning, and critical thinking

  • Product & engineering

• What I think this means

  • What this means for agencies and growth (and by that token Ballpoint)

  • What this means for employees

• Closing thoughts

Anything shared at this stage is really a reflection of current understanding. And so more so than anything else I encourage all of you to research this yourself and form your own viewpoint.

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The job market today

A lot of this conversation can often be too abstract. And so today I want to really go through specifics for our industry.

First let’s consider the current state of the employment market.

The IPA release the annual Agency Census2 data in February. Key insights from it:

1. Employment in creative and non-media agencies is down 14.3%

2. Overall agency headcount is down 6.7%

3. Part time headcount is down 9%

4. Under 25s is down 19.2%

5. Open job roles decreased 41% down to 680

6. Graduate recruitment is 56% down

7. 24% of agencies expect to reduce workforce this year due to AI

Jack Dorsey just reduced headcount at Block by 4,000 down to 6,000. Block haven’t replaced those jobs yet he just knows its coming and is pre-empting.

This pattern is being seen across the wider economy. Job vacancies are down and layoffs are happening, in large part, due to the expected impact of AI rather than its current state. And as the Economist reported last week, we have yet to see the AI impact in macroeconomic data on productivity3.

The current wave of job cuts, when AI is referenced, for now seem to be excuses.

And you can tell this because when you talk to people in different industries, when you hear how the economy is still working, you know that the world is not yet AI-native.

Defining “AI-native” or “AI first”

I’ve been mulling on the idea of what being AI-first means or being AI-native. I see this as the following:

AI-Native. adjective.
Definition: 'Someone whose starting point for problem solving is giving the job to AI, rather than asking AI to help them with their own solving of that task.’

For the last month, I’ve been spending at least two-to-three hours a day, seven days a week experimenting with AI. I’m already blown away.

AI has been able to either (A) dramatically reduce time of a task, or (B) do something to a level we never would have been able to do without.

But importantly my default is not ‘ask how AI can help’ but ‘instruct AI to do the job.’

So what does this look like today?

We’re less than a year away from AI being able to do up to 90% of the current jobs

When I think about the strategic and executional work we to do in growth, performance marketing, and as an agency today, I think we’re months away from AI being able to do all of it.

The more I’ve used Claude Code, the more I’ve seen how much it can do. And I don’t think it’s there yet, but the leap from today until that point now feels measurable. It also may be something we can already achieve, if we put enough work into it.

I imagine within the next few months, if not by the end of the year, we’ll be in a place where almost all the current types of work that performance marketing entails will be significantly improved by AI.

I imagine the time required will go down by maybe 25-90% depending on the task itself, and capacity for what’s possible will increase infinitely.

But where are we today?

Here are a couple of specific use cases I’ve played around with recently.

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Creating a handover podcast for a client

Background
We were migrating one client from one growth strategist to another. This is a process that historically requires the departing growth strategist complete a handover.

The old way

• Sitting down and from memory writing out what the last 3, 6, 12 months looked like

• Rewatching recordings of the quarterly/half-yearly reviews or the ‘Bigger’ meetings like strategy resets, and adding more specific notes from those to the handover

• Doing a load of fresh long term data analysis, getting charts showing monthly performance for the last year

• Taking screenshots from reports and dashboards

• Doing a summary of key players and providing verbal background to it

• Summarising creative wins

• Sitting down and drafting a long memo or deck

• Sharing the deck. Getting the person to read it

• Meeting to discuss

Done well, it’s probably 8-16 hours of work for the person creating the document.

Anyone looking at this methodology knows it’s flawed.

Humans are choc-a-block full of biases. Our brains prioritise and store information relative to those biases. And so we will inherently leave so much context out during this process.

The AI-native way

Flipped around, I wondered if there was a better way to solve this.

I’m a huge fan of the Acquired podcast series: an entire business story including an investment thesis over a four-hour period. There’s a strong narrative interspersed with business analysis. It’s captivating, you actually listen to it as entertainment, and retain more because humans like stories.

We’ve got 3 years of:

• Growth meeting recordings

• Experiment writeups (~1,000)

• Meta, Google, Shopify, COGS data in BigQuery

• Internal and client-facing Slack conversations

• Growth models and forecasts

So I fire open Claude Code, stick it in GSD planning mode and begin discussing the problem at hand.

My initial prompt was something like this.

“I need you to help prepare for me a 45-60m handover podcast. One of my colleagues is departing and another taking over their account. I think the Acquired podcast series is exceptional at podcast storytelling for business stories and I want us to take inspiration from that. You can connect to the Fathom MCP to access all of the call archives (there’s about 150 of them, so you’ll need a good systematic way of analysing them all), there’s Notion where there’s over 1,000 experiments (again with lots of depth, video, statics included, so please take that into consideration), Slack conversations – both with the client and our own internal, recognising the nuances between those two, my Google Drive contains lots of individual reports often needed for annual reviews and one-off reports, and their BigQuery database contains data from Meta, Shopify, with key reports on acquisition, growth, and LTV. The podcast should take the form of a two way conversation with one person the knowledgable expert, and the other an inquisitive newbie. I imagine you’ll use Elevenlabs for the generation itself.”

GSD now went back and forth on clarifying questions. We went quite specific in certain areas as to what we should include in the final output.

I should point out, I’ve got a claude.md file set that explains how Ballpoint work as an agency, types of work, and importantly a writing style guide that was generated on over 100,000 words of copy I’ve written by hand.

About 20 minutes in, I realised this should be a repeatable process and so I interrupted it to tell it to turn this into a skill.

The output was great. I was going to skim listen to it to QA it but ended up listening to all 45 minutes because it was genuinely captivating. As CEO, I couldn’t possibly have this level of context of a client anymore, but every single sentence spoken was so rich in information I felt like I lived through the choices, the turns, the ups, the downs of that client’s journey (and our relationship with them).

The person who received the podcast said it was the most comprehensive podcast she’d had so far. As a bonus we had a knowledge file which she could now quiz and ask questions to: a knowledgebase informed by 100 hours of interviews, 1,000 experiments, and thousands of messages.

It took me four hours to make this. But this was probably my fifth proper AI project. I’m confident I could get to it again now in less than an hour. It also is now reusable.

This was 2-4x faster than the old way, but infinitely better in terms of output.

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Identifying product focus based on retention, LTV and cross-sells

Another brand we work with has hundreds of SKUs across dozens of categories. We’ve long tracked LTV and cohort retention. It is after all that LTV we use to inform what the CM3 target should be.

But we’ve never sat and really analysed those customer journeys.

Why?

There’s also no real plug and play SaaS that does this. No company’s product catalogue is uniform enough for this. Sure if you’re a single-product LTV, out-of-the-box Shopify plugins will give you an answer, but beyond that you’re out of luck.

And for us to do it would cost a lot and take up a lot of time. It’s what I always think of as ‘exploration mode’ in data analysis. You don’t quite know what you’re looking for but you’re giving room to be inquisitive.

But in a client-agency relationship when its effectively paid on time, it’s harder to warrant a cost for something that might yield no results.

The AI-Native way

AI doesn’t have these time limitations.

So once again, I open up Claude Code, I get into gsd:plan mode and start explaining what I want to do.

“Client X has hundreds of SKUs across dozens of categories. They anecdotally find a lot of their customers migrate between product categories as their knowledge and needs expand. But it’s very difficult to analyse this. We want to know if there are clear user paths through products, if there are patterns we can analyse, and therefore see if there’s different ways we can market or focus with retention. Additionally, we want to find out payback and LTV per product. I imagine you’ll want to connect via the BigQuery MCP to access the tables we have we have these tables xxxx, yyyy, zzzz that contain CM2 per order info, spend levels, and product categories. We’re connected to the Shopify API so if we need extra data not in those tables already we can grab that too, just let me know.”

Again this took me maybe 3 or 4 hours to get a decent output for it. Still a large amount of time, but this is because I’m doing this while learning. Now I’ve gone through this process I can prompt better and faster.

The result in this case was identifying some products which seem to have better payback periods and LTV profiles that *aren’t* the key area of focus, so we’re now validating this and seeing if the pattern remains with new focus. Are those entry products correlative or causal?

Let’s find out.

I write twice weekly here every week. This is the weekly Tuesday essay: a key learning from my 16 years experience growing consumer businesses. Every Friday is a weekend debrief: key stories, stats, and reads for the weekend.

Posts are (currently) free, but the archive is paid.

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The new skills we need to learn

Taste, multi-disciplinary learning, and critical thinking

Scott Barker wrote in his Substack last week on How to prepare for the next decade4.

There’s lots in there to dissect from a mental health, identity, and career mindset. But pulling out some practical elements to do with skills for work, I thought this section was great:

“What happens when the skill you spent your life learning can be done at 80% proficiency by a novice in a matter of minutes. We’re already there across most disciplines. AI and robotics will eventually flatten all surface-level skills.

The skills that will matter in the future will be things like judgement, taste, the ability to make connections across disciplines, story telling and moral/ethical reasoning. Going back to the car example, the skills you will need will more closely mirror a navigator than that of the actual driver.

Taste, judgement, cross-disciplinary connections, story-telling and moral reasoning are much harder to foster. These require life experience, failures, interests in many different areas and a lot of time spent in contemplation. It will require you to understand how you actually view the world, what you stand for and who you are.”

Reading this I remarked on how well place people in growth will be.

Growth to many is just rebranded marketing. But I’ve always seen it much deeper.

• Growth mindset comes from Carol Dweck and is the idea that you can constantly self-improve and learn, and abilities are not fixed

• Growth in tech brings together multiple functions of marketing, product, data, and engerineering

• We’re storytellers by nature in our advertising and copy

• We’re visual by nature

There is still lots to learn. Taste is something that needs to be learnt through experience. Reasoning requires active work. And judgement comes by default from experience.

How do we build a world where we foster this stuff together?

So much of this also fits into the adaptation to harder skills as well.

Last year, when I called for the death of the t-shaped marketer, I did so because I thought that old version was too narrow. Instead, I called for the creation of the ‘growth artisan’.

This is the idea that a single person could grow something from start to finish. In current terms that means Shopify, conversion, customer, copy, ads, measurement.

Already with AI, knowledge is at our fingertips, but soon the ability to create within those disciplines will be as well.

As we all play with AI within our current areas of expertise, we know that out of the box, the context is to hallucinatory and broad to be useful. But with the right degree of context, memory-setting, and relevance, it becomes powerful.

Product, design & engineering

I asked Claude Code if I should learn to code the other day, and it told me I didn’t. I did smile at that.

Whether or not I need to, only time will tell.

But I know that being a nerd and someone who broadly understands concepts of TCP/IP, networks, the internet, the web, databases, and high-level computational science has been useful for me as I go.

Having grown up messing around with the command line helps too.

So too does the fact that I used to sit next to a graphic designer, am good friends with a product designer, and I flirted with the idea of being a product manager.

Having some grounding in those functions has been useful. And I believe it’s going to be beneficial for anyone using AI to understand them to some degree.

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What I think this means

What this means for employees

If we look 10 years out, I don’t think there’ll be an AI advantage. It’s available to everyone. And currently there’s no switching costs between the core platforms.

As it currently stands, I fundamentally believe that learning to use AI properly is going to be the same as how everyone had to learn to use a computer. There will be people better at it than others, but if you want a job you just need to know how to use it.

We’re dedicating a lot of time internally to get everyone up to speed on Ai.

We’re not hiring a chief AI evangelist. We’re not outsourcing this. We’re not going to create a function responsible for it.

It’s in everyone’s OKRs. It’s on everyone’s roadmap. It’s in everyone’s progression plan.

We’re betting that everyone has to become AI Native, not just a handful of people in each company.

If we hit OKRs, then by about mid-summer, we should be a fully AI-Native agency.

I think businesses that don’t do this eventually will go extinct. Lots will go out of business, and they’ll get replaced by native/first businesses.

When we look at those job stats, when we think about the future Matt Shumer writes about, and the preparedness that Scott Barker encourages upon is, a few things become clear:

1. The nature of ‘work’ will change forever

2. We are all going to have to reskill

3. Junior team members are going to be hit the hardest and so will need the most support

4. We need to change the internal view of what success looks like

5. Lots of jobs will go

Like many others before, I’d encourage anyone reading this to go deep soon.

What this means for growth (and agencies)

So much AI narrative at the moment is about cost reduction. But to me that doesn’t play out too much.

a16z are looking for AI native agencies, and the reason being is that for the first time agencies could have software like margins at scale.

It feels a bit like that’s a view of agencies from those who haven’t dealt with demanding clients. If they had, they’d know that no client is ever going to let their agency get away with 90% margins. Long term, it just doesn’t feel like there’s a business case for cost-efficient focused agencies.

For me, I see more excitement as we did in my LTV example above. We are at day zero with our AI work, but already it’s enabling us to do things that we just couldn’t have done before.

There are services I’d love for us to offer because I know they’re in the interests of the client, but the client maybe can’t afford them, or we can’t hire the person for a short budget or one-off project to do it. And so the work doesn’t get done. AI solves this.

And then we have the longer term view. In a few years time, when everyone has access to this. Once the great resettling has separated the wheat from the chaff, and the AI-refuseniks go out of business, what happens then?

If advertising is about how we sell products to consumers, then creativity is how we do that and stand out against our competitors. That need won’t ever change. Humans will always desire more, and when they do they’ll always buy more. Companies will always want to sell more and beat more competition. And so the need to stand out remains. Creativity is the answer, we will all just be more excitingly armed.

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Closing thoughts

This feels like the most exciting period of my career to date. It also feels like one of the most anxiety-inducing ones. What I’ve become deeply aware of this last month is that we can no longer keep our head in the sand.

At Ballpoint, we have already begun the work of trying to internally revolutionise. This to me feels like the ‘go mobile’ moment at Facebook all those years ago.

Personally, I’m experimenting with almost every spare minute I have. And I encourage everyone close to me, on my team, and more broadly to do the same.

I am a deeply optimistic person, and I remain so. I think there is huge upside to be had. But that is not inevitable, and it won’t just happen to us, we have to take that opportunity ourselves.

I’m going to be writing more this year on how this journey goes.

In the mean time, I’d love to hear what you all think.

Josh

If this sounds exciting to you, then maybe you want to work here? We’re currently hiring for a head of growth level paid social expert, a data engineer and analyst, and a PPC manager to join our London office.

And if you are the CMO at a consumer company that feels stuck and fed up that the current way isn’t working, then maybe you’d like to work with us. We don’t have all the answers yet, but we’re sure as hell going to try find them as fast as possible. If so, drop me an email josh@weareballpoint.com

I’m building Ballpoint: the growth agency I always wanted to hire when I was a DTC founder and before that a head of growth. We have scale brands from £1m → £50m through digital advertising. If you’re looking for support, then you can email me on josh@weareballpoint.com.

In the meantime, if you enjoyed this please consider giving it a like, a comment or forwarding it to a friend.

4

The Wake Up Call

How to prepare for the next decade

🌒 🌓 🌔…

Read more

2 months ago · 2693 likes · 195 comments · Scott Barker

40 years ago computing made the permanent shift away from the command line to graphical user interfaces (Windows, MacOS). I still remember my first computer, a Windows 95 machine, booted into MS-DOS before it loaded the graphical operating system.

And from then on, it’s felt like GUIs were just the permanent default.

The last week I’ve been increasingly using Wispr Flow. At home, I probably only type half the time I did before. And even in the office, I’m starting to dictate and narrate more than write.

Wispr Flow (Get a month free) is by far most powerful feeding prompts into Claude. Claude feels particularly intuitive at deciphering stream of consciousness. As opposed to using Wispr Flow to dictate emails or Slack messages for example, where often I find I need to add an extra layer for formatting/tone.

Is the future world one where computers are there effectively as command lines and voice commands? Or in reality is computer use actually just going to decrease in general?

I also do worry about the impact this has on using your brain. As I’ve written before, I am a true believer that writing helps you think. And while I’m loving AI’s efficiency gains, if this creates brain rot it’s a serious consideration.

Next week, my colleagues Ryan and Mark will be taking over the reigns. As ever, please share feedback. This is a new format and we want to know. Huge thanks to Maddie and Steve for feedback on the last issue.

We’re currently hiring:

• Head of Growth with paid social specialism (£70-90k)

• PPC Manager (£50-60k)

• Data Engineer & Analyst (£50-60k)

Reply if you want more info.

Have a great weekend,

Josh

Key stat

Signals

Key signals for builders, growers, and operators.

• Sydney Sweeney is back at American Eagle reminding us ‘comment sections are not customers’ [Marketing strategy] – amid all the fury, backlash, and counter-backlash last year, American Eagle’s sales rose 6% to $1.4bn in Q3. Every talking ahead said it was a disaster, but the numbers tell a different story. Last week, Sydney Sweeney rang the bell at the NYSE cementing their partnership. A good reminder not to get too swept up in the online if what you’re doing is true your own brand values.

• We tested the 103 year old Claude Hopkins theory of specificity [Meta Ads / Psychology / Copywriting] this week – and discovered that it still holds true. If you want one simple edit to do to your ads today: read them back and make any claim or promise hyper specific. You’re not reducing market size, you’re improving CPA.

• Protein continues to rise [Health / product strategy] – protein had a great 2025 rising 4.6% in grocery sales, but 2026 looks set to be even greater. The nutrient gap of GLP-1 users is part of the reason, but so too is the new found strength-focused health kick as we reported in our 2026 forecast. In the most elite circles, skinniness is no longer the status single du jour: being strong is.

• Podcasts can take 5.5 months to show their full impact if you’re a high consideration product [Measurement] – Haus’ Olivia Kory shared this excellent graphic for how long your incrementality window should run for depending on channel and consideration.

The stack

A shortlist of stuff I recommend you read and listen to this weekend.

🎧 ‘Keely Hodgkinson’s Insane Year’ High Performance Podcast
📝 ‘The Annual Letter | Palantir Technologies’ The Annual Letter
📝 It turns out you can live a Huel-only diet. Book review by Felicity Lawrence, FT (£).
📝 ’Should I dress like my younger co-workers?’ Vanessa Friedman, New York Times (£)
📝 ’Why Ruggable’s Lauren Sherman is focused on resetting the balance of brand and performance marketing’. Anna Hansel, Modern Retail
📝 ’Why AI companies are suddenly worried about theft’ John Hermann. NY Mag (£)
📝 ’The evolution of advertising in China’. Eliza Williams, Creative Review (£)
📝 ’Velocity is the new authority’. Om Malik
📺 ’Meet the student with no teachers, no homework, just AI’ Every Podcast

Forward to a friend

If you like this, I’d love for you to forward it to a friend. And please, hit reply, hit the like button, leave a comment and let me know what you think.

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Certain truths are always good to re-test. One truth we’ve always known and followed is that specificity outperforms generics every day of the week.

But it’s always good to revisit these things and ensure they remain true today. Lots of classic advertising advice is permanent, some as outdated their working practices.

Over the last month, we’ve ran a handful of tests where in each example we made sure to include a ‘specific’ version and a broader concept version.

In every single test, the specific version outperformed generic version.

• “B12” beat “blood biomarkers”

• “Hot toddy” beat “hot evening drink”

• Calling out “expensive habit” beat product features

There is a juxtaposition at play in tests like this. Jargon is always one of the great villains of copywriting, and so you never want to stray too close to it.

I’ve also heard the arguments against this historically. Namely that by being niche, you reduce your audience size. And so there’s an argument for being broad and that means generic.

But that’s backwards. The greatest joy of today’s Meta world is that its targeting algorithm is powerful. You create a niche ad, Meta finds the audience for it.

Your copy’s job is to signal who the ad is for, and some of the data we’re looking at now confirms this.

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The copy guides the algorithm

Meta knows who to show your ad to. It knows what websites people are browsing. It knows what Reels they’re paying attention to.

I’ve started going to the gym recently and last week was the real turning point when my Instagram algorithm updated to feature gym content and memes. I don’t understand it yet, but I feel like I’ve been let in.

How you interact on Instagram organically has a direct impact on what ads you get served. How you interact on other websites has a direct impact to.

So it knows if you’re interested in classic cars, A line dresses, or international money transfer.

It also knows exactly where you are in that journey. It knows if you’re purchased the entry level product and its time for the upgrade.

Your copy’s job is to stop the right person mid-scroll and confirm that this ad is for them. Generic language can’t do that. “Blood biomarkers” doesn’t trigger anything personal. But “B12” makes someone think *oh, I’ve been meaning to check that.* That’s the difference between scrolling past and stopping.

I used to see this at Wine List too. When we really called out the frustration someone had with not understanding wine menus in restaurants, the ads clicked.

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Creative examples

With Thriva, we’ve been testing being specific and highlighting individual biomarkers like “b12” over more generic “blood biomarkers”.

With Mother Root, that might mean using the “hot toddy” as a specific callout. As I discovered during the call, a hot toddy has both regional, national, and age interpretations of what it is.

Not everyone knows what a hot toddy is, and that’s okay. For the right audience, it hits them exactly where you need to.

As for one from the archives where the AB test was extreme:

We wanted to see if “Pay” outperformed “pay £15” (or other variations). The specific message outperform generic, every time.

This is classic advertising principles

The advertising pioneers figured this out a century ago.

Claude Hopkins was one of the first.

He gave side-by-side examples that read exactly like our test results:

“Our lamps give 33% more light” beats “Our lamps are brighter.”

“Used by the people of 52 nations” beats “Used the world over.”

And critically, he understood the self-selection piece too:

“Blind, irrelevant or clever headlines may attract a larger number of people, but most of the additional people attracted will invariably turn out to be unqualified to buy.”

That’s the 1923 version of “the copy guides the algorithm.”

John Caples in the excellend Testing Advertising Methods was a fan too.

A building materials company he wrote for advertised that their product was “52.7% higher than the U.S. Government standard of quality.”

The campaign was enormously successful.

Then management softened the number to “over 50%.”

Demand collapsed.

As Caples put it: “’52.7%’ was accepted as definite proof of quality and value, while ‘over 50%’ was discounted as a mere claim.” The precision of the number was the persuasion.

Joseph Sugarman made the same point with a simpler example: “Instead of saying ‘There are a lot of nerve endings at the bottom of your feet,’ you can say, ‘There are 72,000 nerve endings at the bottom of your feet.’ You are stating a fact as opposed to a general or vague statement.”

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Why brands get this wrong

The instinct is understandable. The more niche you are, the fewer people you can reach. And isn’t the reason we advertise t reach new people? Well yes, but also no.

No. Because you’re confusing message reach with message resonance.

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Drayton Bird nailed the diagnosis in the excellent Commonsense Direct and Digital Marketing:

“…Sloth being the unwillingness to spend time working out how to describe something accurately. Cowardice being a lack of faith in what is being sold. And presumption because the writer presumes people know what you are selling simply because there is a picture of it, or a vague description.”

He’s right. Generic copy is easier to write, safer to approve, and assumes the creative will do work it can’t actually do.

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How to find the specific language

Oddly, in a world where AI can scrape Reddit in a heartbeat and summarise Trustpilot reviews in seconds, specific language is harder and harder to find.

We believe customer interviews to be the richest source of specific language. It’s why we’re now doing interviews regularly for our clients. Never doubt the learning and impact that a 30 minute conversion can have.

Ogilvy was a fan of the factory visit. Famously, he visited the Rolls-Royce factory and interviewed everyone to come up with his famous line:

“At 60 miles an hour, the loudest noise in this new Rolls-Royce comes from the electric clock.” - David Ogilvy

In both cases, we believe that human research is the most vital stage. Estimations and summarisation and projections can do a lot, we use AI there too. But this is one of those human elements that is vital for ad success.

Read your ad out to your friend. Perhaps the find part to help narrow down your language is to read the ad to someone you know. Not someone who works on the brand, but someone who does a normal job. Say to them the generic thing and see if that’s how people really speak, you’ll realise quickly where the gaps are.

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What this means for your creative briefs

Your creative briefs should be getting more specific, not broader. The best-performing ads historically and today across our entire roster all had one thing in common: they sounded like one person talking to another, not a brand talking to a segment.

If you’re selling protein crisps, then say “I’ve been trying to hit 110g of protein per day” and not “I want a healthier snack.”

If you’re selling French butter in the UK, say “I first spread beurre d’isigny on a baguette sat in a cafe in Nice” and not “this butter reminds me of France.”

If you’re selling light bulbs, say “At 800 lumens, you actually feel like you’re in The Ludlow Hotel” not “low lighting creates a better vibe.”

The algorithm will find the ad its natural home. And when it does the increase in conversion rate for the specificity will outperform the generic all the time.

What’s the most specific version of your product’s message? I’d love to hear what you’re testing.

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

→ Profitably grow paid social spend from £20k/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

Email me or visit Ballpoint to find out more.

NB: We support brands spending above £20k/month.

❤️‍🔥 Subscribe to our Substack to learn how to grow yourself

… because agencies aren’t for everyone, but our mission is to help all exciting challenger brands succeed and so we give away learnings, advice, how-tos, and reflections on the industry every week here in Early Stage Growth.

Every Tuesday, I share an essay to help you grow, and every Friday I share a bitesize roundup of all the news impacting consumer growth, as well as essential reading for the weekend.

I first got a computer when I was eight years old in 1996. I spent hours on that thing, playing around with every nook and cranny of that Windows 95 shell. Briefcase, Publisher, the Registry. There was no stone unturned.

Four years later, I got the internet and built my first PC. An old friend from primary school emailed me to tell me he’d coded a website in HTML. I was jealous and felt stupid. And so I went and bought a book on HTML and spent every spare hour after school and on the weekends learning to build my own. A month later, I discovered View sourcecode and learnt that he’d built it in a website generator. I’d been hoodwinked, but I was hooked on the internet.

12 years after that and I’m in my first job and amazed that I get to do stuff with the internet for a living. Facebook, Foursquare, Livejournal. We’re now connected properly and more widely. It’s not just me and the other internet weirdos in IRC rooms.

And now it’s today. After spending three hours a day on Claude Code for a fortnight, I’ve never been as excited to use a computer, nor as anxious and uncertain as to what that means for all of us.

The mad thing is that the stuff that eight year old me was excited about on that first PC, I could probably vibe code in half an afternoon. Can’t help but wonder where we’ll be in another two decades.

Key stat

Signals

Key signals for builders, growers, and operators.

• It’s time to become generalists [Careers] – Marc Andreesen said there’s a Mexican standoff now that PMs, designers, and engineers could all do each other’s jobs. Boris Cherny, the creator of Claude Code said what we all need to do now is to “try to be a generalist.” I wrote about this last year when I said ’it’s time we all became growth artisans’.

• Why marketing calendars are for the brand that have already made it [Consumer / Meta] – with Meta you have a set number of shots on goal you can take each month. If you’re doing less than £2.5m of revenue, then whatever you do don’t start filling those marketing calendar events.

• Meta’s ‘test-inside-an-adset’ tool is being pushed hard [Meta Ads] – since last October, you’ve been able to test creative inside a scaling campaign. But it’s being heavily pushed this year. We’re running a dozen tests on this as we speak, and we’ll be reporting back in a few weeks with the findings.

• eBay is buying Depop from Etsy for $1.2bn [Consumer] – eBay is worried about younger consumers and so has bought the fashion marketplace from Etsy.

• The end of ‘super-sized’ in the US may be upon us [Consumer] – with everyone from KFC and Olive Garden to high-end restaurants slimming down their portion sizes. The reason is two-fold: GLP-1s and cost of living. Though we must remember the affordability crisis is misunderstood.

The stack

A shortlist of stuff I recommend you read and listen to this weekend.

🎧 ‘Fame is not a business model’. Operators
📝 ‘Dr. Peter Attia steps down from David Protein after Epstein links’ Reuters
🎧 ‘Neuroscience of why we crack under pressure.’ NPR
📝 ’How to solve any problem.’ George Mack / High Agency
📝 ’Don’t ban teenagers from social media.’ Economist (£)
📝 ’Why Nudge Policies Failed’ Rob Wolfe, The Atlantic
📝 ’What Olympic branding teaches us about emotional design’ Creative Review (£)
📺 ’Google DeepMind chief warns AI investment looks ‘bubble-like’ FT Interview

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For a long time, if you said to someone you worked in marketing, the immediate image was of someone planning monthly events, launching campaigns, and so-called activations.

For some sectors and companies sizes, this is a great strategy. Apple events are a series of magical moments throughout the year. The Superbowl most recently on our minds, is a singul…

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Welcome to Aggregate #001. I’m giving the Substack a serious upgrade this year.

Every Tuesday – as you have done for the last three years – you’ll get my usual essay.

This is a seven minute read sitting under one of these six core themes: founder mindset, paid social, growth stories, data & insights, creative & psychology, and growth frameworks.

But…

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Over the last 18 months, we have introduced awareness spend and upper funnel thinking into some of our clients strategies. We did it because every one of these clients was at a ceiling where if we pushed spend, CPA went up.

The results have been pretty powerful – and also for me, incredibly surprising.

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The metric most DTC brands optimise for is actively working against their growth. Here’s what to focus on instead — and a free calculator to get started.

In my first head of growth role, I reported purely on CPA. Along with ROAS, it can be one of the worst metrics in performance marketing.

I didn’t know any better. I genuinely believed we were heading towards a world where platforms would have perfect attribution: where every touchpoint in the customer journey was tracked, and some multi-touch model would assign a precise value to each part of your marketing. For most of the mid-2010s, it looked like that was exactly where things were going.

Then we started testing new channels, and the real problem with this approach became impossible to ignore.

At the time, I could hide behind the fact that measurement genuinely looked like it was heading in that direction. But I really wish I knew then what I know now.

Later, when I became a founder, I understood this problem instinctively, but never properly articulated it. And that’s the issue for most brands: the language we use to talk about performance keeps the entire business stuck in the wrong conversation.

Here’s why ROAS is the worst metric in performance marketing, and the metrics to focus on that will help you grow (and your CFO will love you for it too).

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ROAS teaches you the wrong lesson

In the classic advertising sense, ROAS makes you focus on efficiency rather than effectiveness. That sounds like a subtle distinction. It isn’t. It fundamentally shapes every decision you make.

Efficiency is about minimising waste. Effectiveness is about your ability to achieve an outcome. And the strategic outcome we should all be striving for is growth.

ROAS makes you believe the goal is the most profitable return per customer acquisition. Actually, the goal is to generate more net profit for the business, and to do that you need more contribution margin, not a higher ratio.

Meta is a scale channel, not an efficiency one.

ROAS tricks you into thinking you can maintain high profit per order forever, but eventually you exhaust the low-hanging fruit. The retargeting audiences, the branded search terms, the people who were going to buy anyway. These are your easiest conversions, but they’re also the ones with the lowest incrementality. I.e., if you turned off your campaigns, you probably would have had much of the same result anyway.

Byron Sharp’s research makes this point clearly: most of a brand’s growth comes from acquiring the long tail of light buyers. It comes from people who don’t know you yet and aren’t actively searching. Reaching these people costs more per acquisition, but they represent genuine incremental growth. Incrementality research from Haus and others consistently shows the same pattern: the campaigns with the best platform-reported ROAS often have the lowest true incrementality.

Here’s the uncomfortable bit: ROAS is also easily manipulatable. I can give you brilliant ROAS tomorrow by shifting all your spend to branded search. You’ll have a few weeks of beautiful dashboards. But it won’t actually do anything for the business.

CPA sits on the other side of the same coin. It tells you what you paid per customer, but nothing about what that customer was worth, or whether the spend was genuinely incremental.

One important caveat. I’m not arguing that ROAS and CPA are useless. There are minimum thresholds you absolutely need. You should be at least breaking even, either on the first purchase or through strong repeat purchase economics. But above those thresholds, the conversation needs to shift from “how do we improve our ROAS?” to “how much profitable scale can we add while staying above our floor?”

Quick plug

I write a 7-minute read for Substack every week. We manage £20m of ad spend per year, I’ve helped grow eight consumer businesses from £0 to £10m, and have built creative engines that scale for 9-figure consumer brands. Before I ran Ballpoint, I was a DTC founder and ex-operator.

If you’d like the entire archive of our learnings, consider a paid subscription. You get:

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What to measure instead: contribution margin

If ROAS measures efficiency, contribution margin measures effectiveness. It tells you how much cash your marketing is putting into the business after the costs that actually matter.

There’s some jargon to unpick here, but it’s simpler than it sounds. Think of it as three layers.

CM1 is your product margin. Take your average order value, subtract discounts, subtract your cost of goods. This is what you’d earn on every order if nothing else existed. It’s the starting point.

CM2 is your variable margin per order. Take CM1 and subtract the other costs that come with each sale — shipping, payment processing fees, packaging. This is the real margin you earn every time someone buys, before any marketing cost.

CM3 is your margin after marketing. Take CM2 and subtract your cost per acquisition. This tells you whether your marketing is actually generating cash for the business, per customer acquired.

Two numbers matter here. CM3 as a percentage tells you what proportion of revenue survives all variable costs including acquisition. CM3 in cash terms tells you the total gross profit your marketing is generating. This second number — total contribution in pounds — deserves more of your attention. Because just as ROAS can mislead you on efficiency, a high CM3 percentage can disguise the fact that you’d make far more money at a lower percentage but higher volume.

Here’s a simple illustration.

Brand A spends £50k per month with a 4x ROAS and generates £15k in monthly CM3. Brand B spends £150k per month with a 2.5x ROAS and generates £40k in monthly CM3.

Brand B looks worse on every ratio. It’s making nearly three times the profit.

Now layer in repeat purchases. If a customer comes back within six months and buys again — without you paying a new acquisition cost — that repeat CM2 is pure margin added to the original customer. What looked like a break-even first purchase suddenly becomes very profitable over a six-month window.

Measure this on a blended basis first, across all your marketing. Then model it per channel, so you understand where your next marginal pound is working hardest.

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How to calculate it

The maths isn’t complicated. What’s harder is getting all the inputs into one place.

You need your:

• average order value,

• discount rate,

• COGS per order,

• shipping cost,

• payment processing fees,

• total marketing spend,

• CPA,

• LTV over various time periods

I’ve built a free calculator that takes all of these inputs and generates your CM1, CM2, and CM3, then models five different scaling scenarios automatically so you can see exactly what happens to total gross profit as you trade efficiency for volume. It also includes an incrementality worksheet, so you can model what your real CPA might look like once you account for non-incremental conversions. Link at the bottom.

For brands doing this properly, the gold standard is a lightweight data pipeline that combines your COGS data, sales data, and spend data into one unified view.

It doesn’t need to be complex, even a well-structured spreadsheet can do the job at smaller scale. But having these numbers in one place is what unlocks the ability to make real decisions rather than reacting to platform dashboards.

How to present this to leadership

Once you can see contribution margin clearly, the conversation changes completely.

Instead of reporting “we achieved a 3.5x ROAS this month,” which invites the inevitable follow-up “can we get it to 4x?”, you’re saying: “We generated £85k in gross profit from £200k in marketing spend, and our six-month customer value suggests that figure will reach £120k.”

That’s a conversation about investment and scale. Not about squeezing a ratio.

There’s one question every marketer should ask their finance team: what level of gross profit do we need to cover our operating expenses?

When you know that number, you can model precisely how much marketing spend gets you there and all the trade-offs between efficiency and volume. This is the conversation your CFO actually wants to have. They don’t care about ROAS. They care about whether marketing generates enough gross profit to cover its share of the business’s fixed costs and contribute to the bottom line.

Stop reporting ratios. Start reporting cash contribution.

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Thanks

I’ve introduced CM3 to over 30 brands now, and it has been one of the biggest strategic unlocks in thinking through performance marketing. Remember, Meta is a scale channel not an efficiency one.

I’d love to hear your experiences with CM3 in the comments or if you want to email, hit reply and let me know.

Josh

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The Contribution Margin calculator

I’ve put together a contribution margin calculator as a Google Sheet. Plug in your unit economics and it gives you CM1, CM2 and CM3, plus five scaling scenarios that show what happens to total gross profit as you increase spend at different efficiency levels. There’s also an incrementality tab to model what your real CPA might look like when you account for the fact that not every platform-reported conversion was truly incremental.

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Next Thursday, we are launching a new report: The Future of Meta Is Full Funnel

Over the last 18 months, we’ve run multiple experiments moving up the funnel on Meta. The results have been pretty powerful.

Clients where we adopted full funnel strategies have seen:

• 2-5x more monthly spend at target CPA

• Reduced CPMs

• Lower diminishing returns

We’re now bullish on…

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Rich Cousins (Director of Growth, Thriva), Franky Atill (CMO, Jack and Jill) and Sameer Modha (ex-Head of Applied Data Science at Google, now ITV).

I love measurement. But I also love measurement from the perspective of a growth person. And so hearing Sameer discuss things from the inside, Franky discuss it from a servicing side, and Rich from client all grew that knowledge.

A few things that genuinely changed how I think about this stuff:

Franky framed it brilliant, that it’s about going from playing roulette to playing poker. You’re still placing bets. You’re just stacking the odds.

That by itself is a complete reframing of how to think through growth and reminds us that data doesn’t give us answers, it just helps inform them.

Sameer spoke through his experiences at Google, and his new work at ITV. He rightly described the auction mechanics are “beautiful and terrible at the same time.” They’re designed to extract as much value as possible whilst leaving you slightly better off than you would’ve been otherwise.

Just enough for them to say their hands are clean.

Which raises a philosophical question I can’t stop thinking about:

Who actually deserves the lion’s share of margin your business creates?

You — the one seeking product market fit, up at 5am dealing with the operational chaos — or an ad platform?

Hugely thankful to Rich, Franky and Sameer for being so generous with their time and thinking. And to everyone who came along.

Watch or listen along now. If you want to be first to be invited to these events, then make sure you are subscribed:

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Josh Lachkovic is the founder of Ballpoint, a growth marketing agency that helps brands scale from £1-20M ARR. Visit Ballpoint to learn more, or subscribe to Early Stage Growth for weekly insights on profitable scaling.

Note: Ballpoint works with brands looking to grow their spend from £30k per month to £300k per month.

In mid 2025, Haus released its meta-study of Meta ads1. The finding that stuck with me:

ASC performed 9% better than Manual campaigns at experiment midpoint. But 12% worse by the end.

In other words: ASC was quick to pick up low-hanging fruit, but had lower incrementality over time.

This matched what we were seeing. And it raised an obvious question: should…

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