When was the last time anyone questioned the financial outcomes of retention marketing activities?

Going by the logic:

Every action you take must have a future expectation of results...

Nothing should be left to best practices or "experience".

This is the baseline of all good marketing.

And no one should ever settle for less.

Yet this is pretty typical for many agencies...

Trust-me-I'm-an-expert "strategy".

Nurturing customers, meeting the customer where they're at in the journey, personalisation.

Makes sense in theory, but what’s the incremental lift?

Is it the most efficient use of your limited resources?

At the 7-figure mark, trying to break 8-figures, this is an ever more crucial time.

That's what CTC's Global Accelerator Program solves for.

1. Better alignment with traditionally siloed growth <> retention teams.
2. Better agility to support a very dynamic marketing calendar.
3. Better analysis of activities that impact your P&L.

Together with Growth Strategists, Retention Strategists make this work.

At CTC, we always sign our names on the bottom line.

Because we know that’s what it really means to win.

If this speaks to you, let's chat and see if we'll be a good fit for each other.

Josh Tay

How's your email forecast doing?

Question: do you even have an email forecast?

Sending a bunch of emails without an expectation of revenue is dumb.

All forecasts need to be set from top down.

Based on business goals.

Contribution Margin > New vs Returning Rev > Email Rev

Your email contribution must roll up into the big numbers that matter.

Then track the daily and MTD forecast vs actuals.

So you know if you're behind.

If you're behind, bridge the gap ahead of time.

Any email strategy not tied to daily, weekly, monthly goals is not a strategy.

It's probably fluff.

Director of Retention, Common Thread Collective | Building the world’s strongest retention program for 7 & 8 figure DTC brands

4 things you're missing when forecasting email/sms campaign revenue:

When forecasting, you should bias for recency.

But you must also consider seasonality.

Forgetting these will result in revenue expectations being wildly missed. 

That's why we have these built into Statlas:

- Event Effect
- Day Of the Week Effect
- Week Of the Month Effect
- Then a seasonality factor applied on top of it.

And each of these is applied onto our campaign types and subtypes, for us to anticipate revenue for each specific campaign.

Only with accurate revenue expectations can you execute reasonably.

We hold our team to a high standard.

That also means that you can take credit for success.

Because you did everything possible to meet the number you promised.

And no one can take it away from you.

Whoever's ready, step up and DM me your interest to join us at CTC.

When it comes to campaigns, there needs to be a level of offense.

Yes, list fatigue is real.

Yes, deliverability is important.

Yes, content diversification is necessary.

But what's important also is supporting other channels to ensure the business hits targets set.

For far too long, email marketers have been trying to "protect" their channel.

Not realising that the sole existence of these channels is...

To contribute to business growth.

If the mentality is always to hedge downside (and there's merit in that), other channels end up building around the constraints of your email program.

Which doesn't make sense.

All the mitigating factors should already be built into the bigger strategy.

Not about pushing back and saying "no we can't, because it will hurt the list".

But aligning at the beginning of every month on what is reasonable.

To hit channel targets.

So the business can still hit CM goals.

And if not possible, reallocate resources.

Then decide what the gameplan is and how else to support.

Your emails, SMS, direct mail, push notifications, these are levers.

As much as they're not meant to be drivers of growth, they're meant to contribute to growth.

Which means you need to have a clear expectation of financial outcomes.

After which, follow through and uphold the promise.

This might not be a philosophy that every email marketer believes in.

Few agencies are ever built for this model, and they'll fight the change.

But this is the reality of what makes a marketing unit work.

And why we're pushing so aggressively for this shift.

You can't just optimise for your channel.

It's the entire reason why Statlas is built with the ecommerce pyramid of success.

Where everything is viewed top down, not bottoms-up.

In the case of retention...

Every brand must demand their teams be held accountable to targets.

Otherwise that's not a marketing team, it's a very expensive production factory.

So what are you going to do?

Do what's necessary for growth, or live by the old siloed playbook?

With hundreds of active stores in Statlas, our team's got a good enough sample size to come up with benchmarks by business model.

Which we've distilled down into three main types:

1️⃣ Continuity
2️⃣ Cycle
3️⃣ Event

How we balance short term rev goals with long term LTV requirements is a completely mathetical approach.

1. Customer churn rate
- Active customer repeat rate vs Non-active customer repeat rate

2. Natural repurchasibility
- One-time order vs repeat order bias

3. First order value
- How much of your LTV does your FOV typically make up

This determines if you track 60-day or 180-day or 365-day repurchase rates.

Then there's a subset of levers within each of those sections.

All of this is built into our methodology.

Whether you're a 7-figure brand or 8-figure brand working with our retention team.

Data integrity + tech enablement + department alignment

Acquisition : Retention aligment is the only way.

New rev expectation vs prev month > Pre-purchase flows

Factor in proportion of new and returning visitors.

Returning rev expectations vs prev month > Post-purchase flows

All actualised every month.

Without insight into Growth Plan, how do you know where you're going to land?

Where you want to be ≠ Where you're likey to be

The execution of bridging actuals and projections, against targets is what determines success.

Every brand must hold their agency or email team accountable to revenue.

And that's why at CTC, we build in an element called Ad Hocs.

This is flex resourcing every month.

Behind on email/sms actuals relative to targets?

Deploy ad hocs to meet the plan.

Behind on returning revenue and need to maintain CM?

Growth team liases with retention team to deploy ad hocs to meet the goal.

The success of your business should not be held hostage by the internal constraints of the email agency you hired, or the reactiveness of your email person.

Your team should be tracking daily, weekly, MTD revenue contribution.

Then proactively anticipating shortfall.

If you have a big marketing moment next week that you anticipate can make up for the shortfall?

Cool.

Otherwise, deploy ad hocs.

This is the way.

You should never look at a snapshot of a single month to make any inference on the strength of your retention program.

This is where your Net Active Customer Report is essential.

General rule of thumb:
Net active customers > Churned = Customer file size growth

But these come with caveats.

Example 1:
Don’t just prematurely celebrate success just because you have positive growth.

If majority of net active customers is NEW customers, you have not done a good job at retention.


Example 2:
Just because you have increasing churn # doesn't mean you’re doing a bad job.

If new customers are flooding in, it’s also natural that there will be larger # of churned customers. So look at churned as a % of total active.


Example 3:
If you recently implemented proactive winback campaigns (not just a winback flow), and see increased reactivated customers, that’s a positive sign.

Your next step is to prevent people from even churning, which means targeting the At-Risk customer segment


Example 4:
If you have high Active New + High Churn, Net Active might look flat. 

But your real audience is volatile and retention is actually very weak. 

Then you combine this with your churn prediction by percentile

Then next it's taking context from your customer churn prediction.

Which is based off your product cycle.

---
Some of these reports and tech enablement tools make a world of difference in understanding next steps on execution.

And having all the NECESSARY actionable tools built into one central platform.

Every tool will have different calculations.

Making tech consolidation ever more important.

To have a single source of truth, all with similar parameters for a more accurate understanding of how you're trending.

More emails = More money

True to a certain extent, with a few caveats.

First thing to consider is the impact of volume per week/per month, for each major segment type you're sending to.

Repeat for email and for sms.

And measure it against:

- Positive metrics like click rates
- Negative metrics like unsubscribe rates
- Revenue based metrics like your RPR

If all else remains constant, history is likely to repeat itself.

Scatter plot analyses help a great deal here.

With a regression line to determine the correlation between X and Y axis.

Then look at concentration and location on the chart.

This is step 1 in balancing impressions from more campaigns and balancing deliverability.

In step 2, you start looking at trends over time.

- Impact during marketing moments
- Impact during evergreen periods

Step 3, do your forecast and determine if your account can stomach the volume.

If no, other channels have to pick up the slack.

This is why cohesion of departments is so important.

It's 2026.

No one's got time for siloed marketing.

As much as being behind on forecasts is bad, being too far ahead isn't good too.

Sure, more money is good.

Definitely better than no money.

But too much email rev right now could mean squeezing the sponge.

Where you bring forward revenue that should have been realised at a later month.

This could mean a negative impact on returning rev in the future.

When you're pacing too far ahead, pull back.

You need to be ruthless in staying close to the forecast.

Not beating it for a dopamine kick now.

Because it very well might kick you in the ass real hard later.

Trying to winback churned customers is hard.

Save rate is low. 

And expensive to reacquire.

You have to go upstream.

Look at your at-risk customers.

Go multi-channel if necessary to reach out to customers.

Email, sms, direct-mail, web push, mobile push etc.

Based on our data model, we get our inputs.

This feeds into our net active customer report.

After executing, you should be tracking the impact on your customer file.

That pulls into a customer segment tracker to show % of reactivated, % one-time customers, % two+ customers etc, tracked bi-weekly.

Then observe trend line over time to see the downstream effects.

Why has no one questioned the incrementality of email and sms?

Or any retention effort to begin with.

There's so much focus on meta, tiktok, snapchat, applovin incrementality.

How many have looked into the real contribution of retention activities?

5 day open and click on klaviyo. 

Everyone complains how it's inflated.

If that's true, how and why are you reporting on them?

Not all products have LTV baked into them.

For these brands, you can't have the same LTV growth rate expectation over the next 60-180 days.

One of our clients sells furniture.

People who buy, buy during a new home reno or refurbishment.

After that, there's no real need to buy again.

Trying to use emails to upsell would be a futile effort.

Even if you gave 80% off, there's just literally no reason to repurchase.

So you need to start looking at frontloading the LTV by increasing first order value instead.

There were many things we wanted to do, and will be testing.

- Quiz finder with product recommendations
- Interactive "room builder" with AR features
- Bundle tests
- Cart drawer upsells
- free gift with threshold + progress bars in cart drawer

In this case, we worked on post-purchase upsell funnels first.

It’s important that retention teams work with growth teams on this.

Because you can’t magically make LTV appear from thin air. 

Definitely not by sending a few emails

This is one of the beauties of having your teams synced.

People who are going to buy, are going to buy however they want to.

You can influence it to a certain extent.

But you don't control it as much as you think you can.

We see 3 product highlight campaigns.

Of which, you realise that the actions taken on your target product has a much lower response rate than you'd expect.

And we see this remain consistent across different product/collection focused campaigns.

This isn't just peculiar to this one brand.

It's across our entire portfolio of clients.

So there are three things you can do:


1️⃣ Only send to people who have shown interest before

Tactic: Hypersegment with tight product interest definitions

Pro: Max engagement, likely higher RPR

Con: Miss out on potential rev from other profiles


2️⃣ Send to people who have broad similar interests

Tactic: Engagement window-based collection interests, frequently purchased together

Pro: You get more impressions, high degree of insights from audience breakdown

Cons: Mid engagement


3️⃣ Continue sending to general engagement segments

Tactic: General engagement window, product interest segments added on

Pro: Max recipients, likely higher total campaign rev

Cons: Engagement lowest, likely lower RPR

*Note: You can choose to split further into prospects vs customers etc, but that's not the purpose of this post.
---

Here's how I think about it.

I'd be most hesitant to go with option 1.

While there is merit in content relevancy, we also lose out on opportunity from profiles who aren't "logically" in-market.

I usually go with option 2.

Email is very much also a top-of-mind game.

People will buy whenever they want to, just like how they will buy however they want to.

You have to balance resource efficiency with revenue generation.

And for most, you have limited bandwidth.

Unless you have capability to send 4 campaigns per day to micro segments, that is.

Otherwise, keep volume high (within reason), and just ship it.

Honestly, you don't need another email/sms audit done.

Neither do you need a design refresh because it's not meeting "best practices".

What you need are 3 things:

1. Alignment

Your channel goals must come from your CM and revenue targets.

Your retention team must know how you're pacing every day and week.

2. Accountability

Your team must set an expectation of future financial outcomes.

You must hold them accountable to the number. No excuses.

If they're unwilling to commit, that's not partnership.

3. Agility

Your team – growth, media buying, retention, all must be flexibile.

This comes also with alignment, but the ability to reallocate quickly and efficiently whenever you're too far ahead of behind.

All three are quantifiable.

And that's the fairest way to gauge performance.

No finger-pointing at other departments.

You just make it work.

Talking about strategy is one thing.

Ruthlessly executing so you achieve the modelled outcomes is another.

Novelty is one of the biggest purchase drivers.

We're leveraging this with a few brands.

- Site takeover
- New popup design
- Email design update
- Reuse email heros as static ad creative
- Automated direct mail winbacks with seasonal designs

Within a year, you should have your 4 peaks.

But you should have mini-peaks within each month, if not season.

Reschedules and skips are your early warning signs of churn.

We find that a subscriber taking either of these actions, results in ~23% churn risk.

And when someone cancels, save rate is only 2-4%.

While winbacks make sense, it's often too late.

You should be going upstream too.

This combined with your existing MoM subscription retention drop-off...

Tell you that you need something bigger.

Bigger than just setting up more emails in a flow.

Backend subscription offers and "streaks" are the solution.

- deeper discount on big drop-off month(s)
- freebie on big drop-off month(s)
- stack offer with loyalty program to create "switching barrier"

Build them all into your:

- subscription confirmation emails, to pre-empting
- upcoming order emails, reminding of what's to come
- customer portal, gamified with progress bar

This is the same for subscription programs and membership programs.

Aggressively test your offers.

Offers impact your retention rates more than anything.

Test with front-end subscription offers too and do cohort analysis comparisons.

Most marketers don’t have a strategy problem.

They have an execution + accountability problem.

Everyone has “ideas.”
Everyone has “tests.”
Everyone has a “framework.”

But is this the best use of your limited resources right now?

That's why we have ADmission:

> Weekly coaching calls with the CTC team
> 100+ deep-dive training videos
> 50% off 1:1 consulting with specialists
> Discounts on Statlas + partner bonuses
> 30-day money-back guarantee

This is the closest thing to CTC-level support without paying the agency price tag.

BUT...

CTC is shutting down open enrollment on Jan 28.

After that, it’s invite-only.

If you join now, you lock in the lowest price it’s ever been:

$247/mo (down from $347/mo) — for life.

What you’re really buying isn’t “mOrE CoNtEnt.”

It’s access to the same operators and systems that power the agency.

That allow our growth, media buying, creator content, retention, search teams to win time and time again.

28 Jan.

Get in here:

Open article: ADmission Membership is Closing Soon! Secure Your Spot by bit.ly

ADmission Membership is Closing Soon! Secure Your Spot

Scaling eCommerce Brands Through Profitable Acquisition

Driving profitable, scalable growth for 8 and 9-figure eCommerce brands through integrated performance marketing, creative, and data systems.

AFR Fast Starter 2024 | Finalist Melbourne Young Entrepreneur | Startup of The Year | Emerging Agency of The Year

At Blue Sense Digital, we work with 8 and 9- figure eCommerce brands to align growth strategy with financial outcomes and operational leverage.

We work with businesses where marketing, finance, and operations need to be aligned for profitable scale.

Our clients typically operate in:
· Fashion & Lifestyle
· Consumer Goods
· Home & Living

We believe profitable scale depends on three critical levers:

→ Creative Velocity & Diversity
→ Technical Account Structure
→ Data Integrity

By integrating these pillars, we help brands build a scalable acquisition model, tied directly to financial outcomes.

For earlier-stage brands, we share proven frameworks and strategies through educational content and resources:

→ https://www.youtube.com/@bluesensedigital

If you’re an eCommerce leader ready to build your next chapter of growth, let’s connect: 
https://calendly.com/bluesensedigital/exploratory

I promise to honour your time.

Nathan Perdriau

As an ads guy, it hurts to say...
But organic > ads.

40 days of posting on Instagram.

The reach I've generated would cost $67,000 in ad spend.

Zero dollars spent.

Here's What I've Learned:

1. Volume Negates Luck

You can't post twice and expect to go viral.
Consistency compounds.
The more you ship, the more chances you have to hit.

2. No Platform Has a Daily Posting Limit

There's no cap on how much you can post.
Most people post 3x per week and wonder why they're not growing. I now post 10 times a day.

3. Diversity Matters

Don't just talk about one thing one way.
Different formats.
Different angles (tactical, contrarian, personal).
Different hooks (questions, stats, stories).

Variety attracts different segments of your audience.

4. Contrarian Takes Matter

Everyone says the same thing.
"Test more creatives." "Improve your landing page." "Focus on retention."

Say something different.
Challenge common beliefs.

Share what others won't.
That's what stops the scroll.

5. Experience Matters Most

The uncomfortable truth:
I wouldn't have any success with organic content if I hadn't spent 6 years deep in performance marketing.

Content without expertise is noise.
Expertise without content is invisible.

The Order of Operations:

- Do the work for years (build real expertise)
- Run ads to acquire clients and prove your methods
- Document what you've learned through content
- Scale organically once you have something worth saying

You can't skip step 1.

Producing Better Financial Outcomes for 8-9 Figure Brands

I analysed I Love Ugly's ad library (250 ads running).

One thing stood out immediately:

They're leaning HEAVILY into partnership ads.
And most fashion brands are completely missing this opportunity.

Here's what I found...

What They're Doing Well:

- Heavy use of DCO to avoid page limits 
- Zero DPA's (quality over quantity) 
- Partnership content driving their best performance

The Missed Opportunity:

I scrolled through their entire library.

Everything is high-production studio shoots with clean text overlays.

Zero low-fi content. Zero organic-feeling ads. Zero auditory hooks.

Now here's the interesting part:

When I sorted by longest-running ads...

The top performers (some running 3+ years) are ALL high-production.

So their testing shows this works for them.

But there's a gap:

Their fastest-growing category is activewear.
They're pushing it hard with partnership ads.
Activewear lends itself to organic, UGC-style content naturally.

The Play:

Partnership ads are working. Activewear is growing. But they haven't tested low-fi content in this specific vertical.

That's the white space.

If you're running partnership ads but keeping everything polished and produced...

You're leaving engagement on the table.

The best partnership content feels native to the platform.

Not like an ad that happens to feature someone else.

Test organic formats in your fastest-growing categories first.

That's where audience receptiveness is highest.

We ask this in almost every interview:

"What is a good offer?"

Almost no one gets it right.

Here's the framework:
A good offer creates a value discrepancy in the market.

From your perspective as the seller:
Offer Quality = Perceived Value - Your Actual Costs

You want customers to think your product is worth WAY more than it costs you to deliver.

Example: Customer thinks: "This must cost $200 to make" Your actual cost: $40 Selling price: $100

That gap? That's your margin opportunity.

But here's where it gets interesting:
Customers are running the OPPOSITE equation in their heads.

From the buyer's perspective:
Offer Quality = What It Costs You - What I'm Paying

They want to believe you're selling close to cost.

That you're barely making margin.

That they're getting an incredible deal.

This is why 50% off Black Friday sales work so well:

Customer logic: "These normally sell for $100, now they're $50" "The cost to make these didn't just drop in half" "This is an amazing deal"

Demand goes up.

But as a seller? You just torched your margin.

The equation shrinks for you even as it grows for them.

So what's a GOOD offer that works for both sides?

A reframing of value where the consumer believes they're getting enormous value, but your COGS remain low.

An example:

Free sample packs at cost of shipping.

Customer pays $7 shipping. Gets $20+ worth of samples. Feels like they're getting it free.

But that $7 covers your COGS AND your CAC.

You're break-even on acquisition. 

All profit comes from purchase 2 and 3. 

You've maximised perceived value without sacrificing margin.

The principle:

Stop competing on price.
Start engineering perception.

The best offers make customers feel like they're stealing from you...

While you're actually widening your margins.

How we scaled "unscalable" outbound to 120 clients.

Four years ago, we made custom Loom videos for prospects.

Walked through their website, ads, and gave specific recommendations.

Worked great. But we could only make 10 per day.

So we hired a team.

Conversion rates tanked immediately.

Our faces weren't on the videos anymore.

The fix:

1. Scripted every recommendation
2. Recorded our voice and face for each one
3. Editors superimposed our recordings onto prospect footage

Now it looked personal. But the team did the work.

We ramped to 120 videos per day.

Here's what broke at each stage:

Hit 20/day → conversion dropped
- Fixed: Hired better prospectors

Hit 50/day → no new clients
- Fixed: Hired SDRs to call and get videos watched

Hit 80/day → ran out of editors
- Fixed: Hired full-time editors, recorded at 2x speed

Hit 100/day → too complex to manage
- Fixed: Hired outbound manager

The pattern:

Push the system until it breaks.
Find the bottleneck.
Fix it.
Repeat.

This is how you scale anything:
- Paid ads
- Content production
- Outbound systems
- Operations

People said custom videos with 20+ recommendations weren't scalable.

We proved them wrong.

Key lesson:

You can scale the unscalable.

Just identify what's restricting growth and solve that specific constraint.

Ask yourself right now:

What's the one thing stopping me from doubling output?

Then go fix it.

VSL ads in eCommerce are the opportunity right now.

I've seen a VSL recently hit $360K in total spend (one asset).

Here's their structure:
1. Hook with education (not product)
2. Problem agitate 
3. Mechanism explanation (why it works)
4. Objection handling (why past solutions failed)
5. Product proof (UGC, testimonials)
6. Risk reversal (guarantee)
7. Simple CTA

Why this works:
- Feels educational, not salesy
- Removes doubt in specific order
- Pre-qualifies buyers before landing page

I did a full video breaking down exactly how to make a VSL that can hold $100k+ in ad spend. Linked in comments below.

Birthday sales are an easy way to create a spike without feeling salesy. Time them right and they can bridge the quiet months without hurting the brand.

Three things stop creatives from fatiguing...

IM8 did $100M in under 11 months.

80% of their first-time customers are on subscription.

Sounds like the dream, right?

Wrong.

Here's why copying this strategy could destroy your business:

What IM8 Does:

Subscription is the DEFAULT option.
Save 30% messaging everywhere.
One-time purchase? Hidden on a separate page.

I bought their product to test the funnel.

I didn't even realise one-time was an option until I went looking for it.

The Subscription Trap:

Most founders think: "If we get more people on subscription, we'll have higher LTV. Then we can pay more to acquire customers. This is the key to scale."

The math seems obvious.

But here's what the data actually shows:

Your CAC on subscription customers is MUCH higher.

Yes, LTV goes up when you force subscriptions.

But your cost to acquire those customers skyrockets.

And the equation breaks.

What You Should Actually Track:

Don't just look at LTV.

Look at CAC to LTGP (Lifetime Gross Profit within 365 days).

Run this for BOTH scenarios:
→ CAC for one-time purchases
→ CAC for subscription customers

Then compare:
→ Which has better CAC to LTGP ratio?
→ Where's the actual arbitrage?

The Reality:

In 90% of cases I've analysed...

You're better off acquiring one-time customers.

Yes, they have slightly lower LTGP.
Yes, they're not "as high quality."

But you can acquire them SO much cheaper that the arbitrage is better.

Before You Go Subscription-Only:

Test both funnels side by side.

Measure actual CAC (not assumed).

Calculate the 365-day gross profit for each.

Compare the ratios.

If your subscription CAC is 2.5x higher but LTV is only 1.8x higher?

You're losing money on every "premium" customer.

The Framework:

1. Run split traffic: 50% subscription-default, 50% one-time-default
2. Track CAC for each cohort separately (not blended)
3. Measure LT GP at 90, 180, and 365 days
4. Calculate the CAC to LTGP ratio for both
5. Scale whichever has better unit economics

Subscriptions don't save struggling businesses.

Better margins do.

Know your numbers before you commit to a model that might be bleeding you dry.

Traffic campaigns feel cheap, but they are cheap for a reason...

Paid ads is for acquisition.

Not retention.

Here's why:

At least 70% of returning customer revenue comes from:
- Email
- SMS
- Direct traffic
- Social (organic)

Your most loyal customers return to your website naturally to see new product drops.

They don't need ads to come back.

This is where most brands get confused.

They measure paid ads against total revenue.

That's fundamentally wrong.

Paid ads don't drive all your revenue.

They drive new customer revenue.

The metrics shift:

Instead of MER (total revenue / total ad spend)

Use Acquisition MER (new customer revenue / ad spend).

This applies to every metric:
- ROAS → new customer ROAS
- CPA → new customer CPA
- Profit contribution → new customer profit

Everything should be measured against acquisition only.

Example:

If you're spending £100K on ads and generating £400K in total revenue, your MER is 4x.

But if only £250K came from new customers, your actual acquisition MER is 2.5x.

That's a massive difference in how you should be evaluating performance.

Caveats:

Fashion brands are different.

High product drop rates mean you need some retention spend.

But for most businesses?

You're spending way too much on retention through paid ads.

Focus retention efforts on:
1. Email flows and campaigns
2. SMS campaigns
3. Loyalty programs
4. Organic social

Focus paid ads on:
1. Acquiring new customers
2. Testing new audiences
3. Scaling what works

Stop conflating the two.

Measure them separately.

Optimize them separately.

Creative is everything in 2026, but most training doesn’t teach you how to actually make a good ad...

Recessions consolidate to the top.

Great businesses thrive.

Weak ones collapse.

We're seeing this play out right now.

Ad accounts that were crushing 2 years ago with zero fundamentals are struggling.

No creative strategy.
No retention systems.
Just cranking Meta budgets and hoping for the best.

It worked when CPMs were cheap and demand was high.

Now those brands are hitting £10M/year and falling apart.

Here's what's breaking:

Their MER is dropping.

They audited their business and realized:
- No retention system in place
- Terrible cohort lift after acquisition
- Creative thrown in randomly with no strategy
- Heavy discounting to spike revenue

Now their entire customer base only buys on discount.

Margins squeezed from 70% to 40%.

All of this compounds.

The brands that survive recessions are the ones that built on fundamentals:

1. Strong unit economics
Contribution margins above 60%.
Can afford to acquire customers profitably at scale.

2. Retention systems
Email flows, SMS, subscriptions, loyalty programs.
Not just hoping people come back.

3. Strategic creative production
Angle testing, offer testing, message-market fit.
Not random UGC hoping something sticks.

4. Pricing discipline
No training customers into discount dependency.
Promotions are strategic, not desperate.

When times are easy, bad strategy gets rewarded.

When the market tightens, fundamentals win.

If your growth is built on "just spend more on Meta"...

You're in trouble.

Fix your fundamentals before the market forces you to.

Third-party attribution tools aren't that helpful.

Here's why:

Attribution is unknowable.

These tools try to identify the first click that leads to a purchase.

But they don't pull you back far enough in the journey to reliably show where spend should go.

So why do people think they're amazing?

Because their platform setup is wrong in the first place.

Third-party tools just expose the flaws in your account structure.

Example 1: Meta attribution

You log into Triple Whale.

Meta says 5x ROAS.
Triple Whale says 3x ROAS.

Suddenly you have clarity: "That's why we can't scale past 3x on incremental spend."

But you didn't need Triple Whale to tell you this.

The issue?

Your Meta attribution is set to 7-day click + 1-day view.

You're getting massive overattribution from view-through conversions right before purchase.

The fix:

Change campaigns to 7-day click only.

Or just check the attribution breakdown in Meta for 7-day click ROAS.

Problem solved. No third-party tool needed.

Example 2: Google attribution

Google shows 10x ROAS in-platform.

Your third-party tool shows 4x ROAS.

People think: "This tool revealed Google isn't performing well."

The real issue?

Brand campaigns and existing customers are sitting in your PMAX and shopping campaigns.

They're inflating your ROAS.

The fix:

1. Segment brand campaigns properly
2. Exclude existing customers from PMAX
3. Structure campaigns correctly

Numbers will match up. No third-party tool needed.

What third-party tools actually do:

They highlight problems in your account structure.

But they don't solve them.

You still need to fix:
- Attribution windows
- Campaign segmentation
- Audience exclusions
- Account structure

If your setup is clean, platform data is reliable enough.

Stop relying on tools to tell you what your account structure should already show.

Fix the fundamentals first.

High repeat rate ≠ profitable product.

Here's what to track instead:

The Problem:

Most brands look at repeat purchase rates by product and think they've found their winners.

Product A: 17% repeat rate → "This is our hero product!"
Product B: 12% repeat rate → "Deprioritise this one"

But repeat rate alone is meaningless.

What You Should Actually Measure:

Contribution margin lift.

Not just "do they come back?"

But "how much more profit do we make when they do?"

The Framework:

Step 1: Calculate first-time customer contribution margin by product

Step 2: Calculate lifetime contribution margin by product (track 365 days)

Step 3: Find the dollar lift between the two

Step 4: Rank products by margin lift, not repeat rate

Here's Why This Matters:

Let's say you have two products:

Product A:
- 17% repeat rate (looks amazing)
- First purchase GP: $20
- Lifetime contribution margin: $35
- Lift: $15

Product B:
- 12% repeat rate (looks mediocre)
- First purchase GP: $35
- Lifetime contribution margin: $80
- Lift: $45

You'd think Product A is the winner.

But Product B is generating 3x more profit per customer over their lifetime.

That's where you should be aggressive on acquisition.

How To Apply This:

Once you know your contribution margin lift by product:

Adjust your acceptable CAC (Cost to Acquire A Customer) accordingly.

Product with $15 lifetime lift → Cap CPP at $40
Product with $45 lifetime lift → Push CPP to $50+

You can afford to pay more upfront for customers who generate more profit long-term.

The Key Metric:

Stop optimising for repeat rate.

Start optimising for contribution margin lift.

Repeat rate tells you if customers come back.

Margin lift tells you if it's worth acquiring them in the first place.

Why Most Brands Miss This:

Shopify doesn't make this analysis easy.

You need to build your own model that tracks:
- Product-level contribution margins
- First purchase vs lifetime margins
- Repeat rates tied to entry products
- Dollar lift, not just percentage lift

But once you have it?

You'll know exactly which products to scale and which to pause.

The metric that matters isn't how often they buy.

It's how much profit they generate when they do.

A marketing win that does not show up in the P&L is not a win.

Account simplification has gone too far.

Some people are advising brands to run just one Meta campaign.

Terrible advice.

Here's why you need structure:

1. New vs returning customer isolation

Without segmentation, Meta juggles budgets however it wants between these groups.

The result?

Way too much spend on returning customers.

You're paying to remarket to people who would've bought anyway.

You need separate campaigns to control this split.

2. Geo segmentation

If you don't segment by region, you can't:
- Balance sell-through rates across markets
- Manage different 3PLs effectively
- Allocate spend to hit regional revenue targets

One campaign means Meta decides where your budget goes.

Not you.

3. Structured testing

You need structure to run conclusive tests.

Without it, you can't:
- Isolate variables
- Draw clear conclusions
- Inform future decisions

One campaign with everything thrown in = zero learnings.

4. Product margin profiles

Meta doesn't know your gross margins.

It will push whatever converts easiest.

Often that's your lowest AOV product with the worst margins.

If you optimize for "maximize conversions" (the default), Meta will drive you towards the worst profit contribution.

You need campaign structure to prioritize high-margin products.

The fix:

Build structure around:
- New vs returning customers
- Geographic regions
- Product margin tiers
- Testing frameworks

Account simplification is good.

Oversimplification kills profitability.

Don't confuse the two.

Your Facebook ads aren't performing as well as you think...

How we forecast eComm revenue (quantitative + qualitative).

Most forecasts fail because they're purely backward-looking.

Here's our approach:

Layer 1: Quantitative forecast

Two sides:

1. Returning customer revenue (highly predictable)
2. New customer revenue (larger error bars)

For new customer revenue:

Look at every day for the last 2-3 years.

Plot daily efficiency (return on spend) on a graph.

It looks like an exponential line going down.

The more you spend, the lower the return.

Run a logarithmic regression through that data.

This finds the optimal spend level for each month historically.

Now you have a baseline: "If August happened again like the last 3 years, what should we spend?"

The problem:

The future is never the past.

Every model will be wrong.

Layer 2: Qualitative adjustments (human input)

Example adjustments:

"In August last year, we were out of stock in core products. We need to add $100K in revenue to account for that."

"We're launching a new activation. We expect it to hold an extra $10K in spend at X efficiency."

"Black Friday creative tested well. We'll scale 20% harder than historical baseline."

Layer marketing events on top of the baseline forecast.

Why this matters:

Without the qualitative layer, you end up with vague targets like "$2M revenue, $100K spend."

If it doesn't work, you can't diagnose why.

With layered forecasting:

You can say: "We expected $300K from that product launch and it only generated $150K."

Now you have learnings.

You know where to adjust spend allocation going forward.

How to implement this:

1. Pull 2-3 years of daily spend and efficiency data
2. Plot it (spend vs ROAS or spend vs revenue)
3. Run a logarithmic regression to find optimal spend per month
4. Overlay qualitative adjustments (stock levels, launches, activations, seasonal factors)
5. Hold accountability to both revenue expectation and spend allocation
6. Review post-period and refine the model

This gives you:
- A data-driven baseline
- Context for anomalies
- Clear accountability
- Learnings that compound over time

Stop guessing at forecasts.

Build a model that learns.

Alo yoga is absolutely crushing it on Meta...

The goal of ads isn't the highest ROAS possible.

That's how you kill growth.

Instead, focus on maximizing contribution profit.

You're thinking: "Aren't those the same thing?"

No. And here's why it matters:

ROAS relies on attribution.

Contribution profit is tied directly to cash.

The best operators see reality clearly.

When your metrics sit closer to reality (cash, profit), you get:
- Better feedback cycles
- Sharper decisions
- Campaigns that actually move the needle

If you're optimizing for the highest ROAS in Meta or Google...

You're operating further from reality.

Further from your P&L.

Here's the shift:

Bridge your metrics closer to what actually matters.

When you launch a new test or optimize a campaign, you need to know it's impacting the thing you care about.

Simple question:

Would you rather have:
- 50x ROAS but make no money
- 2x ROAS but make £5M in profit

You'd choose the second every time.

So why are you still optimizing for the first?

How to fix it:

1. Calculate contribution profit per order (revenue - COGS - ad spend - shipping - fees)
2. Set this as your north star metric (not ROAS)
3. Build your dashboards around profit, not attributed revenue
4. Optimize campaigns for maximum profit dollars, not maximum ROAS
5. Test new channels and creatives against profit impact, not efficiency ratios

Stop chasing vanity metrics.

Start chasing cash.

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